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Πρόχειρες σημειώσεις από το μάθημα python, 12η διάλεξη, 17 Ιανουαρίου 2019
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lesson_12_draft.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"def get_vowels(word):\n",
" vowels = 'aeiouy'\n",
" for letter in word:\n",
" if letter in vowels:\n",
" yield letter\n",
" \n",
"\n",
"v = get_vowels('alexiptoto')\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'a'"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"next(v)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'e'"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"next(v)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['i', 'o', 'o']"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(v)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['a', 'a', 'i', 'i']"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(get_vowels('askrdamikti'))"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"i\n",
"o\n"
]
}
],
"source": [
"for x in get_vowels('mitsos'):\n",
" print (x)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"import random"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(61, 39)"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"def split(n):\n",
" a = random.randint(1,n)\n",
" return a, n-a\n",
"\n",
"split(100)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-rw-rw-r-- 1 thodoris thodoris 57154352 Jan 17 09:37 /home/thodoris/Downloads/gwas_catalog_v1.0-associations_e93_r2018-12-21.tsv\r\n"
]
}
],
"source": [
"!ls -l /home/thodoris/Downloads/gwas_catalog_v1.0-associations_e93_r2018-12-21.tsv\n"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/thodoris/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2728: DtypeWarning: Columns (23,27) have mixed types. Specify dtype option on import or set low_memory=False.\n",
" interactivity=interactivity, compiler=compiler, result=result)\n"
]
}
],
"source": [
"gwas = pd.read_csv('/home/thodoris/Downloads/gwas_catalog_v1.0-associations_e93_r2018-12-21.tsv', sep='\\t')"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "row index was 65536, not allowed by .xls format",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-47-c867aee1abc4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgwas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_excel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'test.xls'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mto_excel\u001b[0;34m(self, excel_writer, sheet_name, na_rep, float_format, columns, header, index, index_label, startrow, startcol, engine, merge_cells, encoding, inf_rep, verbose, freeze_panes)\u001b[0m\n\u001b[1;32m 1543\u001b[0m formatter.write(excel_writer, sheet_name=sheet_name, startrow=startrow,\n\u001b[1;32m 1544\u001b[0m \u001b[0mstartcol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstartcol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfreeze_panes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfreeze_panes\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1545\u001b[0;31m engine=engine)\n\u001b[0m\u001b[1;32m 1546\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1547\u001b[0m def to_stata(self, fname, convert_dates=None, write_index=True,\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/io/formats/excel.py\u001b[0m in \u001b[0;36mwrite\u001b[0;34m(self, writer, sheet_name, startrow, startcol, freeze_panes, engine)\u001b[0m\n\u001b[1;32m 647\u001b[0m writer.write_cells(formatted_cells, sheet_name,\n\u001b[1;32m 648\u001b[0m \u001b[0mstartrow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstartrow\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstartcol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstartcol\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 649\u001b[0;31m freeze_panes=freeze_panes)\n\u001b[0m\u001b[1;32m 650\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mneed_save\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 651\u001b[0m \u001b[0mwriter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/io/excel.py\u001b[0m in \u001b[0;36mwrite_cells\u001b[0;34m(self, cells, sheet_name, startrow, startcol, freeze_panes)\u001b[0m\n\u001b[1;32m 1516\u001b[0m wks.write(startrow + cell.row,\n\u001b[1;32m 1517\u001b[0m \u001b[0mstartcol\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1518\u001b[0;31m val, style)\n\u001b[0m\u001b[1;32m 1519\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1520\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0mclassmethod\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/xlwt/Worksheet.py\u001b[0m in \u001b[0;36mwrite\u001b[0;34m(self, r, c, label, style)\u001b[0m\n\u001b[1;32m 1086\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;32mclass\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mxlwt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mStyle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mXFStyle\u001b[0m\u001b[0;31m`\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1087\u001b[0m \"\"\"\n\u001b[0;32m-> 1088\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstyle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1089\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1090\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwrite_rich_text\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrich_text_list\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstyle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mStyle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdefault_style\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/xlwt/Worksheet.py\u001b[0m in \u001b[0;36mrow\u001b[0;34m(self, indx)\u001b[0m\n\u001b[1;32m 1140\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mindx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__flushed_rows\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1141\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Attempt to reuse row index %d of sheet %r after flushing\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mindx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1142\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__rows\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindx\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mRow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1143\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mindx\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlast_used_row\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1144\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlast_used_row\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/xlwt/Row.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, rowx, parent_sheet)\u001b[0m\n\u001b[1;32m 35\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrowx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparent_sheet\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 36\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrowx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint_types\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0mrowx\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0;36m65535\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 37\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"row index was %r, not allowed by .xls format\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mrowx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 38\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__idx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrowx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 39\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__parent\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparent_sheet\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: row index was 65536, not allowed by .xls format"
]
}
],
"source": [
"gwas.to_excel('test.xls')"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['DATE ADDED TO CATALOG', 'PUBMEDID', 'FIRST AUTHOR', 'DATE', 'JOURNAL',\n",
" 'LINK', 'STUDY', 'DISEASE/TRAIT', 'INITIAL SAMPLE SIZE',\n",
" 'REPLICATION SAMPLE SIZE', 'REGION', 'CHR_ID', 'CHR_POS',\n",
" 'REPORTED GENE(S)', 'MAPPED_GENE', 'UPSTREAM_GENE_ID',\n",
" 'DOWNSTREAM_GENE_ID', 'SNP_GENE_IDS', 'UPSTREAM_GENE_DISTANCE',\n",
" 'DOWNSTREAM_GENE_DISTANCE', 'STRONGEST SNP-RISK ALLELE', 'SNPS',\n",
" 'MERGED', 'SNP_ID_CURRENT', 'CONTEXT', 'INTERGENIC',\n",
" 'RISK ALLELE FREQUENCY', 'P-VALUE', 'PVALUE_MLOG', 'P-VALUE (TEXT)',\n",
" 'OR or BETA', '95% CI (TEXT)', 'PLATFORM [SNPS PASSING QC]', 'CNV'],\n",
" dtype='object')"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas.columns"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DATE ADDED TO CATALOG</th>\n",
" <th>PUBMEDID</th>\n",
" <th>FIRST AUTHOR</th>\n",
" <th>DATE</th>\n",
" <th>JOURNAL</th>\n",
" <th>LINK</th>\n",
" <th>STUDY</th>\n",
" <th>DISEASE/TRAIT</th>\n",
" <th>INITIAL SAMPLE SIZE</th>\n",
" <th>REPLICATION SAMPLE SIZE</th>\n",
" <th>...</th>\n",
" <th>CONTEXT</th>\n",
" <th>INTERGENIC</th>\n",
" <th>RISK ALLELE FREQUENCY</th>\n",
" <th>P-VALUE</th>\n",
" <th>PVALUE_MLOG</th>\n",
" <th>P-VALUE (TEXT)</th>\n",
" <th>OR or BETA</th>\n",
" <th>95% CI (TEXT)</th>\n",
" <th>PLATFORM [SNPS PASSING QC]</th>\n",
" <th>CNV</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>intergenic_variant</td>\n",
" <td>1.0</td>\n",
" <td>NR</td>\n",
" <td>4e-08</td>\n",
" <td>7.397940</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>intron_variant</td>\n",
" <td>0.0</td>\n",
" <td>NR</td>\n",
" <td>6e-08</td>\n",
" <td>7.221849</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2 rows × 34 columns</p>\n",
"</div>"
],
"text/plain": [
" DATE ADDED TO CATALOG PUBMEDID FIRST AUTHOR DATE JOURNAL \\\n",
"0 2015-12-18 25574825 Baurecht H 2015-01-08 Am J Hum Genet \n",
"1 2015-12-18 25574825 Baurecht H 2015-01-08 Am J Hum Genet \n",
"\n",
" LINK \\\n",
"0 www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"1 www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"\n",
" STUDY \\\n",
"0 Genome-wide comparative analysis of atopic der... \n",
"1 Genome-wide comparative analysis of atopic der... \n",
"\n",
" DISEASE/TRAIT \\\n",
"0 Inflammatory skin disease \n",
"1 Inflammatory skin disease \n",
"\n",
" INITIAL SAMPLE SIZE REPLICATION SAMPLE SIZE \\\n",
"0 2,079 European ancestry atopic dermatitis case... NaN \n",
"1 2,079 European ancestry atopic dermatitis case... NaN \n",
"\n",
" ... CONTEXT INTERGENIC RISK ALLELE FREQUENCY P-VALUE \\\n",
"0 ... intergenic_variant 1.0 NR 4e-08 \n",
"1 ... intron_variant 0.0 NR 6e-08 \n",
"\n",
" PVALUE_MLOG P-VALUE (TEXT) OR or BETA 95% CI (TEXT) \\\n",
"0 7.397940 (Opposed) NaN NaN \n",
"1 7.221849 (Opposed) NaN NaN \n",
"\n",
" PLATFORM [SNPS PASSING QC] CNV \n",
"0 Affymetrix, Illumina [~ 5200000] N \n",
"1 Affymetrix, Illumina [~ 5200000] N \n",
"\n",
"[2 rows x 34 columns]"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[:2]"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"#gwas.to_html('gwas.html')"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"104480 /home/thodoris/Downloads/gwas_catalog_v1.0-associations_e93_r2018-12-21.tsv\r\n"
]
}
],
"source": [
"!wc -l /home/thodoris/Downloads/gwas_catalog_v1.0-associations_e93_r2018-12-21.tsv"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['DATE ADDED TO CATALOG', 'PUBMEDID', 'FIRST AUTHOR', 'DATE', 'JOURNAL',\n",
" 'LINK', 'STUDY', 'DISEASE/TRAIT', 'INITIAL SAMPLE SIZE',\n",
" 'REPLICATION SAMPLE SIZE', 'REGION', 'CHR_ID', 'CHR_POS',\n",
" 'REPORTED GENE(S)', 'MAPPED_GENE', 'UPSTREAM_GENE_ID',\n",
" 'DOWNSTREAM_GENE_ID', 'SNP_GENE_IDS', 'UPSTREAM_GENE_DISTANCE',\n",
" 'DOWNSTREAM_GENE_DISTANCE', 'STRONGEST SNP-RISK ALLELE', 'SNPS',\n",
" 'MERGED', 'SNP_ID_CURRENT', 'CONTEXT', 'INTERGENIC',\n",
" 'RISK ALLELE FREQUENCY', 'P-VALUE', 'PVALUE_MLOG', 'P-VALUE (TEXT)',\n",
" 'OR or BETA', '95% CI (TEXT)', 'PLATFORM [SNPS PASSING QC]', 'CNV'],\n",
" dtype='object')"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas.columns"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>JOURNAL</th>\n",
" <th>DATE</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
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" <th>1</th>\n",
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" <th>2</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>Am J Hum Genet</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104449</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104450</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104451</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104452</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104453</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104454</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104455</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104456</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104457</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104458</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104459</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104460</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104461</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104462</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104463</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104464</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104465</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104466</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104467</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104468</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104469</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104470</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104471</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104472</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104473</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104474</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104475</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104476</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104477</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104478</th>\n",
" <td>Nat Genet</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>104479 rows × 2 columns</p>\n",
"</div>"
],
"text/plain": [
" JOURNAL DATE\n",
"0 Am J Hum Genet 2015-01-08\n",
"1 Am J Hum Genet 2015-01-08\n",
"2 Am J Hum Genet 2015-01-08\n",
"3 Am J Hum Genet 2015-01-08\n",
"4 Am J Hum Genet 2015-01-08\n",
"5 Am J Hum Genet 2015-01-08\n",
"6 Am J Hum Genet 2015-01-08\n",
"7 Am J Hum Genet 2015-01-08\n",
"8 Am J Hum Genet 2015-01-08\n",
"9 Am J Hum Genet 2015-01-08\n",
"10 Am J Hum Genet 2015-01-08\n",
"11 Am J Hum Genet 2015-01-08\n",
"12 Am J Hum Genet 2015-01-08\n",
"13 Am J Hum Genet 2015-01-08\n",
"14 Am J Hum Genet 2015-01-08\n",
"15 Am J Hum Genet 2015-01-08\n",
"16 Am J Hum Genet 2015-01-08\n",
"17 Am J Hum Genet 2015-01-08\n",
"18 Am J Hum Genet 2015-01-08\n",
"19 Am J Hum Genet 2015-01-08\n",
"20 Am J Hum Genet 2015-01-08\n",
"21 Am J Hum Genet 2015-01-08\n",
"22 Am J Hum Genet 2015-01-08\n",
"23 Am J Hum Genet 2015-01-08\n",
"24 Am J Hum Genet 2015-01-08\n",
"25 Am J Hum Genet 2015-01-08\n",
"26 Am J Hum Genet 2015-01-08\n",
"27 Am J Hum Genet 2015-01-08\n",
"28 Am J Hum Genet 2015-01-08\n",
"29 Am J Hum Genet 2015-01-08\n",
"... ... ...\n",
"104449 Nat Genet 2018-09-17\n",
"104450 Nat Genet 2018-09-17\n",
"104451 Nat Genet 2018-09-17\n",
"104452 Nat Genet 2018-09-17\n",
"104453 Nat Genet 2018-09-17\n",
"104454 Nat Genet 2018-09-17\n",
"104455 Nat Genet 2018-09-17\n",
"104456 Nat Genet 2018-09-17\n",
"104457 Nat Genet 2018-09-17\n",
"104458 Nat Genet 2018-09-17\n",
"104459 Nat Genet 2018-09-17\n",
"104460 Nat Genet 2018-09-17\n",
"104461 Nat Genet 2018-09-17\n",
"104462 Nat Genet 2018-09-17\n",
"104463 Nat Genet 2018-09-17\n",
"104464 Nat Genet 2018-09-17\n",
"104465 Nat Genet 2018-09-17\n",
"104466 Nat Genet 2018-09-17\n",
"104467 Nat Genet 2018-09-17\n",
"104468 Nat Genet 2018-09-17\n",
"104469 Nat Genet 2018-09-17\n",
"104470 Nat Genet 2018-09-17\n",
"104471 Nat Genet 2018-09-17\n",
"104472 Nat Genet 2018-09-17\n",
"104473 Nat Genet 2018-09-17\n",
"104474 Nat Genet 2018-09-17\n",
"104475 Nat Genet 2018-09-17\n",
"104476 Nat Genet 2018-09-17\n",
"104477 Nat Genet 2018-09-17\n",
"104478 Nat Genet 2018-09-17\n",
"\n",
"[104479 rows x 2 columns]"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[['JOURNAL', 'DATE']]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Writing test55.py\n"
]
}
],
"source": [
"%%writefile test55.py\n",
"import pandas as pd\n",
"\n",
"d = {'a': [1,2], 'b': [6,7]}\n",
"\n",
"\n",
"a = pd.DataFrame(d)\n",
"print (a)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 63,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" a b\r\n",
"0 1 6\r\n",
"1 2 7\r\n"
]
}
],
"source": [
"!python test55.py"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Index(['DATE ADDED TO CATALOG', 'PUBMEDID', 'FIRST AUTHOR', 'DATE', 'JOURNAL',\n",
" 'LINK', 'STUDY', 'DISEASE/TRAIT', 'INITIAL SAMPLE SIZE',\n",
" 'REPLICATION SAMPLE SIZE', 'REGION', 'CHR_ID', 'CHR_POS',\n",
" 'REPORTED GENE(S)', 'MAPPED_GENE', 'UPSTREAM_GENE_ID',\n",
" 'DOWNSTREAM_GENE_ID', 'SNP_GENE_IDS', 'UPSTREAM_GENE_DISTANCE',\n",
" 'DOWNSTREAM_GENE_DISTANCE', 'STRONGEST SNP-RISK ALLELE', 'SNPS',\n",
" 'MERGED', 'SNP_ID_CURRENT', 'CONTEXT', 'INTERGENIC',\n",
" 'RISK ALLELE FREQUENCY', 'P-VALUE', 'PVALUE_MLOG', 'P-VALUE (TEXT)',\n",
" 'OR or BETA', '95% CI (TEXT)', 'PLATFORM [SNPS PASSING QC]', 'CNV'],\n",
" dtype='object')"
]
},
"execution_count": 64,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas.columns"
]
},
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"237 2015-02-23\n",
"324 2015-03-26\n",
"330 2015-03-26\n",
"334 2015-03-26\n",
"650 2015-02-12\n",
"869 2015-02-12\n",
"1434 2017-10-23\n",
"1497 2017-11-01\n",
"1503 2017-11-01\n",
"1511 2017-11-01\n",
"1617 2012-09-01\n",
"1751 2017-11-17\n",
"2069 2016-05-16\n",
"2399 2015-02-12\n",
"3243 2015-10-01\n",
"3537 2015-10-01\n",
"3723 2015-10-01\n",
"4762 2017-10-23\n",
"4763 2017-10-23\n",
"4764 2017-10-23\n",
"5058 2012-12-01\n",
"5084 2012-12-01\n",
"6419 2017-09-01\n",
"8113 2011-08-23\n",
"8132 2011-08-26\n",
"8255 2011-09-11\n",
"8574 2011-10-16\n",
"8607 2011-10-16\n",
"8774 2010-08-05\n",
"8775 2010-08-05\n",
" ... \n",
"103422 2018-08-02\n",
"103425 2018-08-02\n",
"103434 2018-08-02\n",
"103438 2018-08-02\n",
"103446 2018-08-02\n",
"103469 2018-08-02\n",
"103496 2018-10-01\n",
"103497 2018-10-01\n",
"103526 2018-10-01\n",
"103533 2018-10-01\n",
"103561 2018-10-01\n",
"103597 2018-10-01\n",
"103630 2018-10-01\n",
"103636 2018-10-01\n",
"103639 2018-10-01\n",
"103651 2018-10-01\n",
"103695 2018-10-01\n",
"103696 2018-10-01\n",
"103711 2018-10-01\n",
"103721 2018-10-01\n",
"103774 2018-10-01\n",
"103780 2018-10-01\n",
"103804 2018-10-01\n",
"103807 2018-10-01\n",
"103820 2018-10-01\n",
"103821 2018-10-01\n",
"103822 2018-10-01\n",
"103829 2018-10-01\n",
"103874 2018-10-01\n",
"103934 2018-10-01\n",
"Name: DATE, Length: 1826, dtype: object"
]
},
"execution_count": 70,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[gwas['PVALUE_MLOG']>100]['DATE']"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"test = gwas.to_dict()"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(104479, 34)"
]
},
"execution_count": 78,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas.shape"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(1524, 34)"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[gwas[\"DISEASE/TRAIT\"].str.contains(\"Breast\", case=False)].shape"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff60ae1e7b8>"
]
},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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4C9i/C/VERMQoyPb4fkHpbcA+to8o5+8EdrP9/kH3TQeml9OXAj8fY9XrA78Z49cYq36IAfojjn6IAfojjn6IAfojjn6IAfojjvGI4cW2J49006QxVjIUDVG22F8T26cAp4xbpdJM21PH6+tN1Bj6JY5+iKFf4uiHGPoljn6IoV/iqBlDN7puFgCbdJxPAe7tQj0RETEK3Uj0NwJbS9pc0krAwcBFXagnIiJGYdy7bmw/Len9wH8CKwDfsn3beNczhHHrBhqDfogB+iOOfogB+iOOfogB+iOOfogB+iOOajGM+8PYiIjoL5kZGxHRckn0EREtl0QfEdFySfQRXSZpE0kf7XUcsfxKou8CSWv0oM4Vhyhbv3Yc0ZC0vqT3SfoRcDWwYY9D6huS1pb0ycp1riVpyyHKt69U/5aSPiLpK5JOkPS3kl5Yo26YgIle0ruG++h1fMXttSqStKekBcC9ki6TtFnH5csqxbCCpPdKOk7SHoOufapGDKWu7SRdJ2m+pFMkrdNx7YYK9a9Zfg4vBW4AtgK2sL2l7Y90u/4h4tlX0o8k/UbSQknXSNqvYv2blP+HiyUdIWk1SScAvwA2qBjH24E7gPMk3SZpl47L36lQ/weBrwOrALsAq9JMKv2ppNd0u37ozhII3bbLEGUC3gRsDJxeIwhJRy/pElCzRf9PwOtt31bWGbpc0jttX8fQy1F0wzeA1WiS20mSrrE98P15C/D5SnGcDBwLXAccAfxY0ptt/xJY7B1PFzxI8z34FPBj25b0VxXqXYyk9wDvBT4GzCzFU4HjJU0pS5B02+nANcB5wD40/y+3Advbvr9C/QM+Abzc9n2SdgX+TdInbJ9Pnd+R9wA72n5G0j8Dl9h+jaRvABcCO3U7gAmX6G1/YOBYkoB3AB+n+SH6fxVD+Qfgi8DTQ1yr+U5ppYEJabbPlTQXOL/sA1BrksSutrcHkPQvwL9KOh84hHp/bADWsH1pOf6SpJuAS8vCejW+F5+gmQl+MnCGpLMr1Lkkfwe80vbDHWVXStoX+DF1Juusa/vYcvyfkh4AdrH9hwp1d1rB9n0Atm+QtCdwsaQp1PsdmQQ8A6wMrFliuWeoLtduVT7hSJoEHAZ8GLgeeJvtsa5+ubRmAd+3fdPgC5KOqBjHHyW9aKCFVFr2ewMXA4v1SXbJSgMHtp8Gpkv6DHAldd/dSNILbT9aYrlK0ltpWpTrdrty2ycCJ0raguaP3PeBP5H0ceAC27/odgwdNCjJD8T4UNM+qhRE0302UOH9wGqSVi+xLBZflzwuacvyzo7Ssn8Nzf/Pn1Wo/5vAjZKuA/4C+AKApMlAle/BhJsZK+lI4CjgCuB427/uURwvBR62vXCIaxvafqBSHH8JLLT9s0HlawNH2u76uxxJ3wW+29GaHig/AjjZdpVWi6RDgbtKt1Vn+abAp22/p0Ycg+reDjgUeLvtWn94kXQ9MH2In4sdgFNt71ohhruBZ1nCira2t+h2DCWOHYAnbd85qHxFmv+X71WI4c+AbYE5tu/odn2L1T8BE/2zNH2hC1n0bZdofniqPEXvZ5LWs/1Qr+PoB6VF+Vv36Add0roVW66d9b4S+B7wbeAmmt+VXYBpwF/b/nHtmDr16vvSUf/6wEO1fi5KY+Mx278tAyamAnfYnlOl/gmY6F883PVaLXxJw67IafvNleI4HviS7d9ImgqcQ9OKWhF4l+1rasQxTHyvtX15pbo+A5xj+w5JKwOXAjvQPEc51PZ/dbn+PWjepj8L/A3NQ+gtaf4v3m77p92sf4h4NgSOpOmeEM2D0K/VehAq6ZsDGxANKp8CXGr7ZZXi2B04nqab5Djg32g2/XgBze/IpcN8+njUfwzNg/E/AF8CPgL8BNgdOM32P3ezfgBsT6gP4LJex1DiWEjTT/9Rmn63V3d+VIzj1o7jq2gedgG8BJjZB9+neyrWdRvPN16ml+/HCjRvmW+oUP8NwHbAK2h2DnplKd8Z+Enl7/t3+uD/fgbwXeAFHWV/CvwKOKxiHDOB1wEHAo8Au5fybYCbK9R/G82QyvWAx4HJpXx1mq6crn8PJuLD2BG3zarkRcBraR66HQr8ADjTdZZk7rSipEluHoKuavtGANu/KK3arhvm3Y1ofrhrecrlNwh4PXCW7WeAueUBfretaPtWAEkLXbpHbM+StGqF+jv1QxfmYTRDb8+WdDCwG3A28Le2f1Axjkm2LwOQ9Pcuz3DcvPOrUf8ztv9X0lPA/wIPlfqfqPVgfCIm+hdKesuSLroZG9t1JYFcSjN8b2WahH91+UH6ao0Yiq8Bl5QunEslfRk4H9gbmF0phlcBfw38blC5aDaLr+UPkl4GPADsSfMWecBqFervHFb7fwddW4m6VpO0E0sY3mp7VrcDKH90p0v6Cs3s4BcDB3rQw/IKnu04/t9B12r0Xc+SdAZNC/4KYEaZVLcXlSZXTshED7yRJe9NWyXRA5QE/waaJL8ZcFLN+gFsf1XSrcD7aLprJtFstn4B9SYqXUczqmGx5wGSag57PQo4l+Zd34m2f1Vi2A+4uUL9n5a0mu0nbX9/oFDN1PsqE/k6bAycwJJ/T/bqdgCSvlrqEk2XzSzg0DI6Ctsf7HYMxQ6SHitxrFqOKeerVKj/CJpuI9P8fO5K0wvwc5qGWtdNxIexN9vu+kyyUcQxA3gZ8EOaLoIqT8+jf3V0ofVcP/yeSJo23HXbM2rFsrybiIn+NuA9tv+7x3E8CzxRToca5rlW/ahKANKVtrveYhtU5wE0a7vcavs/a9Y9KI6X0jyI3aYUzQVOcYXJSpJm2d65HH/VHbO4a+uTRL8KsKYHzTWRtAHNUMPfV4pjL9tXluPNB97plfO3dLu7V9I+LiN7yvyWE2iGus4B/s4V5txMuEXNgDOBEyTdLekLknbsRRC2X2B7zfKxVsfHmjWTvKRbBn3cCuwxcF4phpNpptyvBxwn6dM16h0ijlfQ9AX/jmaK/6k0f4yvLkPsuh5Cx/EeS7yrjpN7XD80XZmvGqL8tcCJFeP4UsfxeYOu1Vh07x8GxXIfzdpcN9I8rO6+GkN7uvFB82Dn4zR9r3OBzwAv6YO41gY+WbG+i2iGsG1TviebAfPL8YsrxTCHZj0RaB563tSj7/0PgdcMUf5q4IcV6p811HGPvhedsZzXoxhuH+babRXjuHmo46HOK/xfzB50bXa367c9IVv0QDMxyvYX3Lw9PRT4K5qEX4WWvATrnVRcgtXNxKzzaFqwO9i+G/hj+f7UWh7iKTejkLD9JHUXMuu0pe2rBxe6eUhcY7r9Nh3vqrbpfJdV691Vh87/gypLDYwQw2A1c4+XcDzUeTdsIOloSR8G1tKiYyqrfB8m4qgb4Ll1KvahWS1wb5rlUD9XMYQlLcG6nesuwYrtCyRdRtNtcgT1h/Jt05HIBGxZzmsvS/H4MNeeGObaeNm2Qh2jNVxyq+VBSbvaXmQvADXrwS+2RlQXbVHmeqjjmHK+eYX6T6WsWEkziWx9YKGkF1FpCPREfBg7MEnpDTQzEc+iWUWyxi9yZxw/s71Dx/kDwKauvwTrIsoCTq+w/fWKdfbLshQP0vw8LHaJZgmC5WaXJ0nP0PxxE82szCcHLlFpsICatd/PodncY2CV16k06+0cZPv6bsdQ4nj1cNfd42VCapiIif4q4AyafsdeLor0M+A1PP/29KrO81qxSdredu1ugVGRtAJwsCusDljq6+lwPkmPM3TruecjsXqljLA5kmYosmne9f6Lh1j1tRck7WH7J12uYzdgru3HygzpY2iWxbgd+AeXZbW7GsNES/T9Qv2zBOszNGuHnEmzBEO1bQw7YliL5pd5Y5qHw5cD76eZmTrb9v61Y+pUhvm9yfa/9zKO5Y2k/YEptr9Wzm+gmcxm4GO2z60UxwrA22l+Pi+1PUfSG2k2ilnVXR6GWoaE72D7aUmn0Ly7Opemy3kH20uc6T9uMSTRT2ySbgbeSdOddRDN2/UzaSZx3V0phgtpFov6Kc0P7zo0zwmOsl1rGYbBMa1As5DVITTr3lxr+21drnPYzU16+Q60FyT9hOYd3fxyPptmRu4awLdt710pju/Q7NF6A816O7+mWXjuGHfMYO5i/XNtb1uOn5trUc5n2+76EPEJ+zC2H5Wp7gcDh7jSEqw07x7mAJ8EPln6RQ8GrpU03/afV4hhC9vbQbM0Lc3KjZvaHu7haFdI+guaUVgDz3D2ADYvo4G6bWDddwEbAffy/Ds+07vRL72y0kCSL35c/tg9rLLLVCVTafapfba8u/sNsFXFQRNzJL3b9reBn0maanumpJcAf6wRQBL9GEnaiKYlfSjNioH/SNOKrBZC50kZ4XBDGcr1F5VieO6H1c0GyL/qUZJfANxDM1noo7YfL7HUSPLYfm4ERz/MTO0D63Se2H5/x2nNVWifsv1sieH3kn5ReWTcEcBXJH2K5o/MTyXNp5nvUmXb0ST6ZSTpPTQJfQrNyIIjgAtt1xziCc0G5Ytx0ydXazTBwKJRsOjCUbUfQp4HHEDzh/eZ0qXUq77J9InC9ZLeY/vUzkJJ76V5t1VLT4f/loeth0lak+Zd3SRggSttNwrpo19mataW/inwYdszS9ldtR7CxtDKZJQ9af4I7wesBRwOXGJ78DLK3Yxjkb7Y5VEZcfN9mp2VBpZFfjmwMnBArUTXD8N/la0EJyY1e04eSJNQNqRp1R9me5PKccyiWRr5TJdd7vuJpHtsb9qjugcm1R0CvM72+l2u7+iO06OBRbaIc40t4/qQpL1otjOEZumDK3sZT23qg60Ek+jHgZo9MA+mSSirARfY/kSlun9F02XxduB+mhE3Z9u+t0b9IykPhKv88ZO0qe17lnBtVduDN50Y7/o/O9z1HnTrBb2f31CGV06lyQ130wxeWFgeSF9fY+BG+uiXUZnGPd/2/bYXSFoI/A/N93SNiqE8YvsjwEckvYrmj80sSXNpWvmnVIxlKDVbEt+nmYiCpPNsv/W5ILqc5EsdSeR9yPaaI9/VVdlKcAL7BvCX8NyQvn8EPgDsSI/WPLF9Lc2wyg/QLAV7EM1iZ101qMtikUvU/aPXDwt5RQyWrQQnsBU6JsAcRLO5xXnAeWViSC2Lbajhjv1sK8UwXIvpK5VigP5YyCtisMFbCe5G8847Wwn2O0lzgB3LtOY7gOm2fzRwreKEqSj6YSGviH6UFv2yOxO4RtJvaPrdrgWQtBXQ9UWKBpThhJ2thb2A/YE7gK8PTBTpcgyfGeaybR/X7RhKRSvUqGdpSLrY9ht7HUf0jqQ1gI8Bb6WZd/MU8Evg5G4vtPdcDGnRLzs129NtBFzmskxymda8hu1Zw37y+MXwrzQbnawEPEYzRvk/aMaQP2D7qAoxfHiI4tVpxq+vZ7tmP31fyQzZKBP3LgD+i2Z03Oo0y2l/CvifGiP0kugnOEm32t6ujBm/H9jI9lOSJtFsk7Zd5XjWBI6iSfLnACfYfrBmDP1E0rds/02v44jeGWLvihtt7yLpBTTbLW4zzKePiwm7lWA852kA238EbrT9VDl/GnimVhCS1pX0eeAWmi7BnW1/fHlO8gBJ8gE8IemVAJLeBDwMULpVq4yvTB/9xHe/pDVs/872PgOFarYpe6pGAJK+CLyFZijndjWXGoiYAN4HnFq6decAfwMgaTIZdRNjUWbdrV6jRS3pWZrp3U+z6LDGjHaJ6ANJ9C1TnvC/BLjL9m97HU/E8k7SB4HzbS/oVQzpo5/gyqibgeNX0sy0OwG4VdJ+PQtsOSRpBUnvlXScpD0GXftUr+KKnjuOZo+IayX9n9JlU1US/cS3e8fxcTTLv+4JvBr4+96EtNz6Bs33/SHgJEmdqxJ2fV/Q6Ft30YyfP45mmebbJV0qaVoZpdZ1SfTtstbA+H3bdwF9N4Go5Xa1fajtL9NMc19D0vmSVqbS6IroS7b9rO3LbB8O/AnwrzRLaN9VI4Ak+olvG0m3SLoVeImkdQDKGN0VexvacmelgQPbT9ueDswGrqTu4m7RXwZv9/lH2xfZPgSosldDhldOfINXynyivK4LDLc0QYy/mZL2sf3cYnK2/17SvTT72Mby6aAlXaixfDZk1E2rSFqX5m3iI72OJSLtkE3CAAAIf0lEQVSeV9ak2hXYmGYI8r3ADa6UgNN1M8FJ2lTSWWXjk+uBGyU9WMo26210yxdJW0u6UNIcSWdK2rjXMUXvSXodcCdwLM0aVG8APgfcWa51P4a06Cc2ST8FvgycW9ahR9IKNCtafsj27sN9fowfSdcCpwM/At4MvMJ2Rtss58pub/vavntQ+eY0m9Z3faOiJPoJTtKdtrde2msx/iTNtr1jx/ks2zv3MqboPUl3AtuW9ac6y1eiWdRsq27HkIexE99NZdLUDGB+KdsEmAbc3LOolk+rSNqJ50dZrNp5Xmvp6ug736LpUj2LRX9HDwZOqxFAWvQTXGkVHE6z2cjGNEllPs2a9KfZ/kMPw1uuSLpqmMu2vVe1YKKvSNqWRX9HFwAX2a6yZ2wSfUREy2XUTYuNsMVfVCTptb2OIfqPpB9WqSct+vaSdI/tKjPvYnj5v1h+SVrSA3kBF9veqNsx5GHsBCfpsSVdAlatGcvyTtJFS7oErFczlugrNwLXMPR6R2vXCCCJfuL7LbCL7QcGX5A0f4j7o3teBfw1MHiHrYFZkbF8mgu81/adgy/U+h1Nop/4TgdeDCyW6IEzKseyvLsOeNL2NYMvSPp5D+KJ/nAsS34e+oEaAaSPPiKi5TLqZoKT9HpJbxui/B0Z6dE/JP2k1zFEb0g6WtLhQ5R/QNKHqsSQFv3EJuk64E22Fw4qfxFwge1X9Cay6CRpvu1Neh1H1CdpDrCz7acGla8M3Gh7+27HkBb9xLfa4CQPYPt+YPUexBNDS4tq+eXBSb4U/oFKO4/lYezEt4qkSUMsmLQiGV5ZlaQlrVSZoa7LOUkbDh4ZJ2nDWvUn0U985wOnSnq/7ScAJK0OnFSuRT1vGubaxdWiiH7zReAHkj4MDCxs93Lgn4Av1QggffQTnKRJwOeBI4Bf07QeN6FZFe/Ttv/Yw/AiApC0L3AM8LJSNAc43naWQIjRk7QqMLCu9bxae1HG8yR9x/Zh5Xia7Rk9DikCyMPYVpC0AU1r4bM0G4IfU8qirh06jo/qWRTRdyTtK+kaSb+RtLAc71er/iT6CU7SHjRraUAzS/a75fiGci3qydvjWIyk9wDH0ewTuwWwZTk+VtL0KjGk62ZiK+Po32f75kHlOwLfsL1bbyJb/kh6EDiL5jnJQeX4ObY/2Iu4orck3Q680vbDg8rXA35cY8/YjLqZ+NYanOQBbM+WtGYvAlqOfbTjeGbPooh+o8FJHsD2Q1KVYfRJ9C0gSevYfmRQ4bqka66qPHyNJXhM0g62f9ZZKGkH4PEaASTRT3wnApdJ+giLjtH9AvDlnkW1HJL0SmAL26eX83OBdcvlz9u+smfBRS99GLhI0reBm2ie5ewCTKNZ1rrr0kffApLeCHwM+DOaH6LbgS/a/o+eBrackXQF8IGBDZ8l3QocRrMUxSds79PD8KKHyizYI2l+RwXcBnytLFXS/fqT6NtL0odsp1VfiaQbbe/ScX6+7beU45/YziioWISks20f1PV6kujbK/uU1iXpTttbL+HaPNtbDXUtll+1fkfzsK7d6jzSjwF3SHrD4MLStZYdpqJn8jC23fJ2ra6/o1m86m0s+mD8z4E39iyq6ClJOy/pErBilRjSdTOxSXqcoRO6gFVt5495RWUziXfQPHSD5qHbGbZ/37uoopckXTXcddt7dj2GJPqIiHZLay9inIzw7sq216ocUgSQFn1EROtl1E1ERMsl0UdEVCbp2Jr1JdFHRNT35pqVJdFHRNRXdTJjHsZGRFQm6QW2n61WXxJ9RES7pesmIqLlkugjIlouiT4iokckvbtKPemjj4jojVrr0Wetm4iILpJ0y5IuARvWiCGJPiKiuzYEXg88MqhcwH/XCCCJPiKiuy4G1rA9e/AFSVfXCCB99BERLZdRNxERFUlaTdJUSZNr1ZlEHxHRRZLeLOluSbMk7UezveS/ALdKmlYlhnTdRER0j6SfAQcCLwSuAra3fZekDYArbG/X7RjyMDYioruetf0LAEm/sn0XgO0HJT1dI4Ak+oiI7nqBpHVousqfLccDyxRX6T5P101ERBdJuht4liWsQW97867HkEQfEdFuGXUTEdEDkl4q6dQadSXRR0R0kaTtJV0maY6kz0vaUNJ5wBXA7TViSKKPiOiuU4EzgLcCC4FZwF3AVrZPrBFA+ugjIrpI0mzbO3aczwc2s/1MrRgyvDIiortWkbQTz4+6+R2wvSQB2J7V7QDSoo+I6CJJVw1z2bb36noMSfQREe2WrpuIiC6TtB5wKLBNKZoLnGH74Rr1Z9RNREQXSdoWmAO8HPgFcCewCzBH0jbDfe64xZCum4iI7pF0LnCO7XMGlb8VONT2W7seQxJ9RET3SPq57Zcu7bXxlK6biIjuemIZr42bPIyNiOiuDSQdPUS5gCrbCSbRR0R016nAmku49s0aAaSPPiKi5dJHHxFRmaSuL3vQKYk+IqK+IXeb6pYk+oiI+n5Qs7L00UdE9ICkPWgmTB3Z7boy6iYiohJJO9KsefN24FfA+TXqTaKPiOgiSS8BDgYOAR4CzqbpTdmzWgzpuomI6B5JzwLXAofbnlfK7rK9Ra0Y8jA2IqK73grcD1wl6VRJe1N51E1a9BERFUhaHTiApgtnL2AGcIHty7pedxJ9RERdktYFDgQOylaCEREtJuke25t2u5700UdEtFwSfUREy2UcfUREFy1hLXpoRt6sUSOGJPqIiO5a0lr0AF+pEUAexkZEtFxa9BERXSTppOGu2/5gt2NIoo+I6K6bOo4/B3y2dgDpuomIqETSzbZ3ql1vhldGRNTTk5Z1En1ERMul6yYiooskPc7zLfnVgCcHLgG2vVbXY0iij4hot3TdRES0XBJ9RETLJdFHRLRcEn1ERMsl0UdEtNz/B6XCK5WfVjhzAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff60ae792e8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"gwas[\"MAPPED_GENE\"].value_counts()[:10].plot(kind=\"bar\")"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff60ad382e8>"
]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff60addef60>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gwas[\"MAPPED_GENE\"].value_counts()[:10].plot(kind=\"pie\")"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
"gwas['DATE'] = pd.to_datetime(gwas['DATE']) "
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 2015-01-08\n",
"1 2015-01-08\n",
"2 2015-01-08\n",
"3 2015-01-08\n",
"4 2015-01-08\n",
"5 2015-01-08\n",
"6 2015-01-08\n",
"7 2015-01-08\n",
"8 2015-01-08\n",
"9 2015-01-08\n",
"10 2015-01-08\n",
"11 2015-01-08\n",
"12 2015-01-08\n",
"13 2015-01-08\n",
"14 2015-01-08\n",
"15 2015-01-08\n",
"16 2015-01-08\n",
"17 2015-01-08\n",
"18 2015-01-08\n",
"19 2015-01-08\n",
"20 2015-01-08\n",
"21 2015-01-08\n",
"22 2015-01-08\n",
"23 2015-01-08\n",
"24 2015-01-08\n",
"25 2015-01-08\n",
"26 2015-01-08\n",
"27 2015-01-08\n",
"28 2015-01-08\n",
"29 2015-01-08\n",
" ... \n",
"104449 2018-09-17\n",
"104450 2018-09-17\n",
"104451 2018-09-17\n",
"104452 2018-09-17\n",
"104453 2018-09-17\n",
"104454 2018-09-17\n",
"104455 2018-09-17\n",
"104456 2018-09-17\n",
"104457 2018-09-17\n",
"104458 2018-09-17\n",
"104459 2018-09-17\n",
"104460 2018-09-17\n",
"104461 2018-09-17\n",
"104462 2018-09-17\n",
"104463 2018-09-17\n",
"104464 2018-09-17\n",
"104465 2018-09-17\n",
"104466 2018-09-17\n",
"104467 2018-09-17\n",
"104468 2018-09-17\n",
"104469 2018-09-17\n",
"104470 2018-09-17\n",
"104471 2018-09-17\n",
"104472 2018-09-17\n",
"104473 2018-09-17\n",
"104474 2018-09-17\n",
"104475 2018-09-17\n",
"104476 2018-09-17\n",
"104477 2018-09-17\n",
"104478 2018-09-17\n",
"Name: DATE, Length: 104479, dtype: datetime64[ns]"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas['DATE']"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {},
"outputs": [],
"source": [
"import time"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1547713786.2240205"
]
},
"execution_count": 98,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"time.time()"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [],
"source": [
"import datetime"
]
},
{
"cell_type": "code",
"execution_count": 104,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"RangeIndex(start=0, stop=104479, step=1)"
]
},
"execution_count": 104,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas.index"
]
},
{
"cell_type": "code",
"execution_count": 111,
"metadata": {},
"outputs": [],
"source": [
"gwas['x'] = gwas.index\n",
"gwas['y'] = gwas['DATE']"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff647806f28>"
]
},
"execution_count": 119,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff6477cdbe0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gwas[ 'DATE'].plot(style='.',c='red')"
]
},
{
"cell_type": "code",
"execution_count": 123,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>DATE ADDED TO CATALOG</th>\n",
" <th>PUBMEDID</th>\n",
" <th>FIRST AUTHOR</th>\n",
" <th>DATE</th>\n",
" <th>JOURNAL</th>\n",
" <th>LINK</th>\n",
" <th>STUDY</th>\n",
" <th>DISEASE/TRAIT</th>\n",
" <th>INITIAL SAMPLE SIZE</th>\n",
" <th>REPLICATION SAMPLE SIZE</th>\n",
" <th>...</th>\n",
" <th>P-VALUE</th>\n",
" <th>PVALUE_MLOG</th>\n",
" <th>P-VALUE (TEXT)</th>\n",
" <th>OR or BETA</th>\n",
" <th>95% CI (TEXT)</th>\n",
" <th>PLATFORM [SNPS PASSING QC]</th>\n",
" <th>CNV</th>\n",
" <th>my_index</th>\n",
" <th>x</th>\n",
" <th>y</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-08</td>\n",
" <td>7.397940</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-08</td>\n",
" <td>7.221849</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-12</td>\n",
" <td>11.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.2000</td>\n",
" <td>[1.15–1.27]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-11</td>\n",
" <td>10.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>24</td>\n",
" <td>24</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-10</td>\n",
" <td>9.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>31</td>\n",
" <td>31</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-08</td>\n",
" <td>7.522879</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>38</td>\n",
" <td>38</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-08</td>\n",
" <td>7.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>42</td>\n",
" <td>42</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>47</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-07</td>\n",
" <td>6.301030</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>47</td>\n",
" <td>47</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>7e-09</td>\n",
" <td>8.154902</td>\n",
" <td>(Shared)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>57</td>\n",
" <td>57</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>128</th>\n",
" <td>2015-12-18</td>\n",
" <td>25581431</td>\n",
" <td>Kuchenbaecker KB</td>\n",
" <td>2015-01-12</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25581431</td>\n",
" <td>Identification of six new susceptibility loci ...</td>\n",
" <td>Epithelial ovarian cancer</td>\n",
" <td>4,368 European ancestry cases, 9,123 European ...</td>\n",
" <td>2,462 European ancestry BRCA1 mutation carrier...</td>\n",
" <td>...</td>\n",
" <td>9e-14</td>\n",
" <td>13.045757</td>\n",
" <td>NaN</td>\n",
" <td>1.1400</td>\n",
" <td>[1.10-1.19]</td>\n",
" <td>Illumina [up to 10962898] (imputed)</td>\n",
" <td>N</td>\n",
" <td>128</td>\n",
" <td>128</td>\n",
" <td>2015-01-12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>129</th>\n",
" <td>2015-12-18</td>\n",
" <td>25581431</td>\n",
" <td>Kuchenbaecker KB</td>\n",
" <td>2015-01-12</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25581431</td>\n",
" <td>Identification of six new susceptibility loci ...</td>\n",
" <td>Epithelial ovarian cancer</td>\n",
" <td>4,368 European ancestry cases, 9,123 European ...</td>\n",
" <td>2,462 European ancestry BRCA1 mutation carrier...</td>\n",
" <td>...</td>\n",
" <td>6e-51</td>\n",
" <td>50.221849</td>\n",
" <td>NaN</td>\n",
" <td>1.5900</td>\n",
" <td>[1.48-1.70]</td>\n",
" <td>Illumina [up to 10962898] (imputed)</td>\n",
" <td>N</td>\n",
" <td>129</td>\n",
" <td>129</td>\n",
" <td>2015-01-12</td>\n",
" </tr>\n",
" <tr>\n",
" <th>164</th>\n",
" <td>2016-01-31</td>\n",
" <td>25869804</td>\n",
" <td>Ibrahim-Verbaas CA</td>\n",
" <td>2015-04-14</td>\n",
" <td>Mol Psychiatry</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25869804</td>\n",
" <td>GWAS for executive function and processing spe...</td>\n",
" <td>Information processing speed</td>\n",
" <td>Up to 30,807 European ancestry individuals, up...</td>\n",
" <td>Up to 8,436 European ancestry individuals, up ...</td>\n",
" <td>...</td>\n",
" <td>3e-09</td>\n",
" <td>8.522879</td>\n",
" <td>(LDST/DSST- age, sex, and education adjusted)</td>\n",
" <td>5.9200</td>\n",
" <td>[NR] unit increase</td>\n",
" <td>Affymetrix, Illumina [up to 2357391] (imputed)</td>\n",
" <td>N</td>\n",
" <td>164</td>\n",
" <td>164</td>\n",
" <td>2015-04-14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166</th>\n",
" <td>2016-06-17</td>\n",
" <td>26174136</td>\n",
" <td>Setoh K</td>\n",
" <td>2015-07-15</td>\n",
" <td>Nat Commun</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/26174136</td>\n",
" <td>Three missense variants of metabolic syndrome-...</td>\n",
" <td>Serum alpha1-antitrypsin levels</td>\n",
" <td>3,294 Japanese ancestry individuals</td>\n",
" <td>6,065 Japanese ancestry individuals</td>\n",
" <td>...</td>\n",
" <td>3e-16</td>\n",
" <td>15.522879</td>\n",
" <td>NaN</td>\n",
" <td>2.0500</td>\n",
" <td>[1.56-2.54] mg dl-1 increase</td>\n",
" <td>Illumina [6569727] (imputed)</td>\n",
" <td>N</td>\n",
" <td>166</td>\n",
" <td>166</td>\n",
" <td>2015-07-15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>170</th>\n",
" <td>2016-05-17</td>\n",
" <td>26083657</td>\n",
" <td>Stafford-Smith M</td>\n",
" <td>2015-06-17</td>\n",
" <td>Kidney Int</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/26083657</td>\n",
" <td>Genome-wide association study of acute kidney ...</td>\n",
" <td>Acute kidney injury in coronary artery bypass ...</td>\n",
" <td>873 European ancestry cases</td>\n",
" <td>380 European ancestry cases</td>\n",
" <td>...</td>\n",
" <td>5e-07</td>\n",
" <td>6.301030</td>\n",
" <td>NaN</td>\n",
" <td>21.6600</td>\n",
" <td>[13.19-30.13] unit increase</td>\n",
" <td>Illumina [530716] (imputed)</td>\n",
" <td>N</td>\n",
" <td>170</td>\n",
" <td>170</td>\n",
" <td>2015-06-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>174</th>\n",
" <td>2016-04-21</td>\n",
" <td>26025128</td>\n",
" <td>Park HW</td>\n",
" <td>2015-05-27</td>\n",
" <td>J Allergy Clin Immunol</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/26025128</td>\n",
" <td>Genetic risk factors for decreased bone minera...</td>\n",
" <td>Bone mineral accretion in asthma (oral cortico...</td>\n",
" <td>489 European ancestry children</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-08</td>\n",
" <td>7.397940</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Illumina [NR]</td>\n",
" <td>N</td>\n",
" <td>174</td>\n",
" <td>174</td>\n",
" <td>2015-05-27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>182</th>\n",
" <td>2016-07-11</td>\n",
" <td>26121033</td>\n",
" <td>Grondin Y</td>\n",
" <td>2015-06-29</td>\n",
" <td>PLoS One</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/26121033</td>\n",
" <td>Genetic Polymorphisms Associated with Hearing ...</td>\n",
" <td>Noise-induced hearing loss</td>\n",
" <td>19 European and Mexican ancestry exposed indiv...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-07</td>\n",
" <td>6.301030</td>\n",
" <td>NaN</td>\n",
" <td>12.7500</td>\n",
" <td>[NR]</td>\n",
" <td>Affymetrix [289036]</td>\n",
" <td>N</td>\n",
" <td>182</td>\n",
" <td>182</td>\n",
" <td>2015-06-29</td>\n",
" </tr>\n",
" <tr>\n",
" <th>191</th>\n",
" <td>2016-06-10</td>\n",
" <td>26151821</td>\n",
" <td>Schumacher FR</td>\n",
" <td>2015-07-07</td>\n",
" <td>Nat Commun</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/26151821</td>\n",
" <td>Genome-wide association study of colorectal ca...</td>\n",
" <td>Colorectal cancer</td>\n",
" <td>18,299 European ancestry cases, 19,656 Europea...</td>\n",
" <td>4,725 East Asian ancestry cases, 9,969 East As...</td>\n",
" <td>...</td>\n",
" <td>3e-09</td>\n",
" <td>8.522879</td>\n",
" <td>NaN</td>\n",
" <td>1.1400</td>\n",
" <td>[1.09-1.19]</td>\n",
" <td>Affymetrix, Illumina [~ 2500000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>191</td>\n",
" <td>191</td>\n",
" <td>2015-07-07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>192</th>\n",
" <td>2016-06-10</td>\n",
" <td>26151821</td>\n",
" <td>Schumacher FR</td>\n",
" <td>2015-07-07</td>\n",
" <td>Nat Commun</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/26151821</td>\n",
" <td>Genome-wide association study of colorectal ca...</td>\n",
" <td>Colorectal cancer</td>\n",
" <td>18,299 European ancestry cases, 19,656 Europea...</td>\n",
" <td>4,725 East Asian ancestry cases, 9,969 East As...</td>\n",
" <td>...</td>\n",
" <td>2e-08</td>\n",
" <td>7.698970</td>\n",
" <td>NaN</td>\n",
" <td>1.0900</td>\n",
" <td>[1.05-1.11]</td>\n",
" <td>Affymetrix, Illumina [~ 2500000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>192</td>\n",
" <td>192</td>\n",
" <td>2015-07-07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>211</th>\n",
" <td>2016-01-13</td>\n",
" <td>25710614</td>\n",
" <td>Hong X</td>\n",
" <td>2015-02-24</td>\n",
" <td>Nat Commun</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25710614</td>\n",
" <td>Genome-wide association study identifies peanu...</td>\n",
" <td>Milk allergy</td>\n",
" <td>291 European ancestry child cases, 144 Europea...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-06</td>\n",
" <td>5.698970</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Illumina [6459842] (imputed)</td>\n",
" <td>N</td>\n",
" <td>211</td>\n",
" <td>211</td>\n",
" <td>2015-02-24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>217</th>\n",
" <td>2016-01-13</td>\n",
" <td>25710614</td>\n",
" <td>Hong X</td>\n",
" <td>2015-02-24</td>\n",
" <td>Nat Commun</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25710614</td>\n",
" <td>Genome-wide association study identifies peanu...</td>\n",
" <td>Food allergy</td>\n",
" <td>671 European ancestry child cases, 144 Europea...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-06</td>\n",
" <td>5.301030</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Illumina [6459842] (imputed)</td>\n",
" <td>N</td>\n",
" <td>217</td>\n",
" <td>217</td>\n",
" <td>2015-02-24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>223</th>\n",
" <td>2016-01-13</td>\n",
" <td>25710614</td>\n",
" <td>Hong X</td>\n",
" <td>2015-02-24</td>\n",
" <td>Nat Commun</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25710614</td>\n",
" <td>Genome-wide association study identifies peanu...</td>\n",
" <td>Egg allergy</td>\n",
" <td>217 European ancestry child cases, 144 Europea...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-06</td>\n",
" <td>5.397940</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Illumina [6459842] (imputed)</td>\n",
" <td>N</td>\n",
" <td>223</td>\n",
" <td>223</td>\n",
" <td>2015-02-24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>231</th>\n",
" <td>2016-01-31</td>\n",
" <td>25849990</td>\n",
" <td>Tapper W</td>\n",
" <td>2015-04-07</td>\n",
" <td>Nat Commun</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25849990</td>\n",
" <td>Genetic variation at MECOM, TERT, JAK2 and HBS...</td>\n",
" <td>Myeloproliferative neoplasms</td>\n",
" <td>524 European ancestry JAK2 negative cases, 2,6...</td>\n",
" <td>1,383 European ancestry JAK2 negative cases, 4...</td>\n",
" <td>...</td>\n",
" <td>2e-09</td>\n",
" <td>8.698970</td>\n",
" <td>NaN</td>\n",
" <td>1.2200</td>\n",
" <td>[1.14-1.30]</td>\n",
" <td>Affymetrix [2098039] (imputed)</td>\n",
" <td>N</td>\n",
" <td>231</td>\n",
" <td>231</td>\n",
" <td>2015-04-07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>242</th>\n",
" <td>2016-01-22</td>\n",
" <td>25820613</td>\n",
" <td>Warrington NM</td>\n",
" <td>2015-03-27</td>\n",
" <td>Hum Mol Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25820613</td>\n",
" <td>Genome-wide association study of blood lead sh...</td>\n",
" <td>Lead levels in blood</td>\n",
" <td>5,433 individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-06</td>\n",
" <td>5.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1950</td>\n",
" <td>[0.077-0.313] unit decrease</td>\n",
" <td>Illumina [6391392] (imputed)</td>\n",
" <td>N</td>\n",
" <td>242</td>\n",
" <td>242</td>\n",
" <td>2015-03-27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>243</th>\n",
" <td>2016-01-22</td>\n",
" <td>25820613</td>\n",
" <td>Warrington NM</td>\n",
" <td>2015-03-27</td>\n",
" <td>Hum Mol Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25820613</td>\n",
" <td>Genome-wide association study of blood lead sh...</td>\n",
" <td>Lead levels in blood</td>\n",
" <td>5,433 individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-06</td>\n",
" <td>6.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1940</td>\n",
" <td>[0.11-0.28] unit increase</td>\n",
" <td>Illumina [6391392] (imputed)</td>\n",
" <td>N</td>\n",
" <td>243</td>\n",
" <td>243</td>\n",
" <td>2015-03-27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>244</th>\n",
" <td>2016-01-22</td>\n",
" <td>25820613</td>\n",
" <td>Warrington NM</td>\n",
" <td>2015-03-27</td>\n",
" <td>Hum Mol Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25820613</td>\n",
" <td>Genome-wide association study of blood lead sh...</td>\n",
" <td>Lead levels in blood</td>\n",
" <td>5,433 individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-06</td>\n",
" <td>5.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.2760</td>\n",
" <td>[0.11-0.45] unit increase</td>\n",
" <td>Illumina [6391392] (imputed)</td>\n",
" <td>N</td>\n",
" <td>244</td>\n",
" <td>244</td>\n",
" <td>2015-03-27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>260</th>\n",
" <td>2016-01-16</td>\n",
" <td>25839716</td>\n",
" <td>Ng E</td>\n",
" <td>2015-04-02</td>\n",
" <td>Environ Res</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25839716</td>\n",
" <td>Genome-wide association study of plasma levels...</td>\n",
" <td>Polychlorinated biphenyl levels</td>\n",
" <td>922 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-08</td>\n",
" <td>7.522879</td>\n",
" <td>(PCB126)</td>\n",
" <td>1.2300</td>\n",
" <td>[0.8-1.66] unit decrease</td>\n",
" <td>Illumina [8736858] (imputed)</td>\n",
" <td>N</td>\n",
" <td>260</td>\n",
" <td>260</td>\n",
" <td>2015-04-02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>262</th>\n",
" <td>2016-01-16</td>\n",
" <td>25839716</td>\n",
" <td>Ng E</td>\n",
" <td>2015-04-02</td>\n",
" <td>Environ Res</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25839716</td>\n",
" <td>Genome-wide association study of plasma levels...</td>\n",
" <td>Polychlorinated biphenyl levels</td>\n",
" <td>922 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-07</td>\n",
" <td>6.698970</td>\n",
" <td>(PCB138)</td>\n",
" <td>1.1100</td>\n",
" <td>[0.7-1.52] unit decrease</td>\n",
" <td>Illumina [8736858] (imputed)</td>\n",
" <td>N</td>\n",
" <td>262</td>\n",
" <td>262</td>\n",
" <td>2015-04-02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>266</th>\n",
" <td>2016-01-16</td>\n",
" <td>25839716</td>\n",
" <td>Ng E</td>\n",
" <td>2015-04-02</td>\n",
" <td>Environ Res</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25839716</td>\n",
" <td>Genome-wide association study of plasma levels...</td>\n",
" <td>Polychlorinated biphenyl levels</td>\n",
" <td>922 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-07</td>\n",
" <td>6.221849</td>\n",
" <td>(PCB153)</td>\n",
" <td>1.0200</td>\n",
" <td>[0.63-1.41] unit decrease</td>\n",
" <td>Illumina [8736858] (imputed)</td>\n",
" <td>N</td>\n",
" <td>266</td>\n",
" <td>266</td>\n",
" <td>2015-04-02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>267</th>\n",
" <td>2016-01-16</td>\n",
" <td>25839716</td>\n",
" <td>Ng E</td>\n",
" <td>2015-04-02</td>\n",
" <td>Environ Res</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25839716</td>\n",
" <td>Genome-wide association study of plasma levels...</td>\n",
" <td>Polychlorinated biphenyl levels</td>\n",
" <td>922 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-07</td>\n",
" <td>6.301030</td>\n",
" <td>(PCB153)</td>\n",
" <td>0.7600</td>\n",
" <td>[0.47-1.05] unit decrease</td>\n",
" <td>Illumina [8736858] (imputed)</td>\n",
" <td>N</td>\n",
" <td>267</td>\n",
" <td>267</td>\n",
" <td>2015-04-02</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104237</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Pulse pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>249,262 European ancestry individuals</td>\n",
" <td>...</td>\n",
" <td>2e-08</td>\n",
" <td>7.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1154</td>\n",
" <td>[0.075-0.156] unit decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104237</td>\n",
" <td>104237</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104324</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>8e-15</td>\n",
" <td>14.096910</td>\n",
" <td>NaN</td>\n",
" <td>0.2371</td>\n",
" <td>[0.18-0.3] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104324</td>\n",
" <td>104324</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104325</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-14</td>\n",
" <td>14.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.2528</td>\n",
" <td>[0.19-0.32] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104325</td>\n",
" <td>104325</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104330</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.2161</td>\n",
" <td>[0.16-0.28] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104330</td>\n",
" <td>104330</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104337</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-11</td>\n",
" <td>10.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.2092</td>\n",
" <td>[0.15-0.27] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104337</td>\n",
" <td>104337</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104347</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-10</td>\n",
" <td>10.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.3358</td>\n",
" <td>[0.23-0.44] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104347</td>\n",
" <td>104347</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104356</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-10</td>\n",
" <td>9.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1893</td>\n",
" <td>[0.13-0.25] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104356</td>\n",
" <td>104356</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104365</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-10</td>\n",
" <td>9.221849</td>\n",
" <td>NaN</td>\n",
" <td>0.1909</td>\n",
" <td>[0.13-0.25] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104365</td>\n",
" <td>104365</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104376</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Systolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-09</td>\n",
" <td>8.301030</td>\n",
" <td>NaN</td>\n",
" <td>0.1824</td>\n",
" <td>[0.12-0.24] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104376</td>\n",
" <td>104376</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104386</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>7e-15</td>\n",
" <td>14.154902</td>\n",
" <td>NaN</td>\n",
" <td>0.1645</td>\n",
" <td>[0.12-0.21] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104386</td>\n",
" <td>104386</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104387</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-14</td>\n",
" <td>13.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1801</td>\n",
" <td>[0.13-0.23] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104387</td>\n",
" <td>104387</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104391</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-13</td>\n",
" <td>12.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1398</td>\n",
" <td>[0.1-0.18] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104391</td>\n",
" <td>104391</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104394</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1576</td>\n",
" <td>[0.11-0.2] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104394</td>\n",
" <td>104394</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104399</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-12</td>\n",
" <td>11.522879</td>\n",
" <td>NaN</td>\n",
" <td>0.1279</td>\n",
" <td>[0.092-0.164] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104399</td>\n",
" <td>104399</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104401</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-12</td>\n",
" <td>11.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1229</td>\n",
" <td>[0.088-0.158] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104401</td>\n",
" <td>104401</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104402</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-12</td>\n",
" <td>11.301030</td>\n",
" <td>NaN</td>\n",
" <td>0.1207</td>\n",
" <td>[0.086-0.155] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104402</td>\n",
" <td>104402</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104405</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>8e-12</td>\n",
" <td>11.096910</td>\n",
" <td>NaN</td>\n",
" <td>0.1225</td>\n",
" <td>[0.087-0.158] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104405</td>\n",
" <td>104405</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104406</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-11</td>\n",
" <td>11.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1271</td>\n",
" <td>[0.09-0.164] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104406</td>\n",
" <td>104406</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104412</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-11</td>\n",
" <td>10.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1211</td>\n",
" <td>[0.086-0.156] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104412</td>\n",
" <td>104412</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104413</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-11</td>\n",
" <td>10.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1176</td>\n",
" <td>[0.083-0.152] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104413</td>\n",
" <td>104413</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104415</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-11</td>\n",
" <td>10.522879</td>\n",
" <td>NaN</td>\n",
" <td>0.1171</td>\n",
" <td>[0.083-0.152] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104415</td>\n",
" <td>104415</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104425</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>8e-11</td>\n",
" <td>10.096910</td>\n",
" <td>NaN</td>\n",
" <td>0.1444</td>\n",
" <td>[0.1-0.19] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104425</td>\n",
" <td>104425</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104429</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-10</td>\n",
" <td>10.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1470</td>\n",
" <td>[0.1-0.19] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104429</td>\n",
" <td>104429</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104442</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-10</td>\n",
" <td>9.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1142</td>\n",
" <td>[0.079-0.15] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104442</td>\n",
" <td>104442</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104448</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-10</td>\n",
" <td>9.221849</td>\n",
" <td>NaN</td>\n",
" <td>0.1325</td>\n",
" <td>[0.091-0.174] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104448</td>\n",
" <td>104448</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104461</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-09</td>\n",
" <td>8.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1962</td>\n",
" <td>[0.13-0.26] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104461</td>\n",
" <td>104461</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104466</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-09</td>\n",
" <td>8.522879</td>\n",
" <td>NaN</td>\n",
" <td>0.1391</td>\n",
" <td>[0.093-0.185] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104466</td>\n",
" <td>104466</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104468</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1244</td>\n",
" <td>[0.083-0.166] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104468</td>\n",
" <td>104468</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104469</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1364</td>\n",
" <td>[0.091-0.182] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104469</td>\n",
" <td>104469</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104478</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-09</td>\n",
" <td>8.301030</td>\n",
" <td>NaN</td>\n",
" <td>0.1394</td>\n",
" <td>[0.093-0.186] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104478</td>\n",
" <td>104478</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>14812 rows × 37 columns</p>\n",
"</div>"
],
"text/plain": [
" DATE ADDED TO CATALOG PUBMEDID FIRST AUTHOR DATE \\\n",
"0 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"1 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"5 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"20 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"24 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"31 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"38 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"42 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"47 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"57 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"128 2015-12-18 25581431 Kuchenbaecker KB 2015-01-12 \n",
"129 2015-12-18 25581431 Kuchenbaecker KB 2015-01-12 \n",
"164 2016-01-31 25869804 Ibrahim-Verbaas CA 2015-04-14 \n",
"166 2016-06-17 26174136 Setoh K 2015-07-15 \n",
"170 2016-05-17 26083657 Stafford-Smith M 2015-06-17 \n",
"174 2016-04-21 26025128 Park HW 2015-05-27 \n",
"182 2016-07-11 26121033 Grondin Y 2015-06-29 \n",
"191 2016-06-10 26151821 Schumacher FR 2015-07-07 \n",
"192 2016-06-10 26151821 Schumacher FR 2015-07-07 \n",
"211 2016-01-13 25710614 Hong X 2015-02-24 \n",
"217 2016-01-13 25710614 Hong X 2015-02-24 \n",
"223 2016-01-13 25710614 Hong X 2015-02-24 \n",
"231 2016-01-31 25849990 Tapper W 2015-04-07 \n",
"242 2016-01-22 25820613 Warrington NM 2015-03-27 \n",
"243 2016-01-22 25820613 Warrington NM 2015-03-27 \n",
"244 2016-01-22 25820613 Warrington NM 2015-03-27 \n",
"260 2016-01-16 25839716 Ng E 2015-04-02 \n",
"262 2016-01-16 25839716 Ng E 2015-04-02 \n",
"266 2016-01-16 25839716 Ng E 2015-04-02 \n",
"267 2016-01-16 25839716 Ng E 2015-04-02 \n",
"... ... ... ... ... \n",
"104237 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104324 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104325 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104330 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104337 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104347 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104356 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104365 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104376 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104386 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104387 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104391 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104394 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104399 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104401 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104402 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104405 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104406 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104412 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104413 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104415 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104425 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104429 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104442 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104448 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104461 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104466 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104468 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104469 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104478 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"\n",
" JOURNAL LINK \\\n",
"0 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"1 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"5 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"20 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"24 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"31 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"38 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"42 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"47 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"57 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"128 Nat Genet www.ncbi.nlm.nih.gov/pubmed/25581431 \n",
"129 Nat Genet www.ncbi.nlm.nih.gov/pubmed/25581431 \n",
"164 Mol Psychiatry www.ncbi.nlm.nih.gov/pubmed/25869804 \n",
"166 Nat Commun www.ncbi.nlm.nih.gov/pubmed/26174136 \n",
"170 Kidney Int www.ncbi.nlm.nih.gov/pubmed/26083657 \n",
"174 J Allergy Clin Immunol www.ncbi.nlm.nih.gov/pubmed/26025128 \n",
"182 PLoS One www.ncbi.nlm.nih.gov/pubmed/26121033 \n",
"191 Nat Commun www.ncbi.nlm.nih.gov/pubmed/26151821 \n",
"192 Nat Commun www.ncbi.nlm.nih.gov/pubmed/26151821 \n",
"211 Nat Commun www.ncbi.nlm.nih.gov/pubmed/25710614 \n",
"217 Nat Commun www.ncbi.nlm.nih.gov/pubmed/25710614 \n",
"223 Nat Commun www.ncbi.nlm.nih.gov/pubmed/25710614 \n",
"231 Nat Commun www.ncbi.nlm.nih.gov/pubmed/25849990 \n",
"242 Hum Mol Genet www.ncbi.nlm.nih.gov/pubmed/25820613 \n",
"243 Hum Mol Genet www.ncbi.nlm.nih.gov/pubmed/25820613 \n",
"244 Hum Mol Genet www.ncbi.nlm.nih.gov/pubmed/25820613 \n",
"260 Environ Res www.ncbi.nlm.nih.gov/pubmed/25839716 \n",
"262 Environ Res www.ncbi.nlm.nih.gov/pubmed/25839716 \n",
"266 Environ Res www.ncbi.nlm.nih.gov/pubmed/25839716 \n",
"267 Environ Res www.ncbi.nlm.nih.gov/pubmed/25839716 \n",
"... ... ... \n",
"104237 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104324 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104325 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104330 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104337 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104347 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104356 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104365 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104376 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104386 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104387 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104391 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104394 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104399 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104401 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104402 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104405 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104406 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104412 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104413 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104415 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104425 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104429 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104442 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104448 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104461 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104466 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104468 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104469 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104478 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"\n",
" STUDY \\\n",
"0 Genome-wide comparative analysis of atopic der... \n",
"1 Genome-wide comparative analysis of atopic der... \n",
"5 Genome-wide comparative analysis of atopic der... \n",
"20 Genome-wide comparative analysis of atopic der... \n",
"24 Genome-wide comparative analysis of atopic der... \n",
"31 Genome-wide comparative analysis of atopic der... \n",
"38 Genome-wide comparative analysis of atopic der... \n",
"42 Genome-wide comparative analysis of atopic der... \n",
"47 Genome-wide comparative analysis of atopic der... \n",
"57 Genome-wide comparative analysis of atopic der... \n",
"128 Identification of six new susceptibility loci ... \n",
"129 Identification of six new susceptibility loci ... \n",
"164 GWAS for executive function and processing spe... \n",
"166 Three missense variants of metabolic syndrome-... \n",
"170 Genome-wide association study of acute kidney ... \n",
"174 Genetic risk factors for decreased bone minera... \n",
"182 Genetic Polymorphisms Associated with Hearing ... \n",
"191 Genome-wide association study of colorectal ca... \n",
"192 Genome-wide association study of colorectal ca... \n",
"211 Genome-wide association study identifies peanu... \n",
"217 Genome-wide association study identifies peanu... \n",
"223 Genome-wide association study identifies peanu... \n",
"231 Genetic variation at MECOM, TERT, JAK2 and HBS... \n",
"242 Genome-wide association study of blood lead sh... \n",
"243 Genome-wide association study of blood lead sh... \n",
"244 Genome-wide association study of blood lead sh... \n",
"260 Genome-wide association study of plasma levels... \n",
"262 Genome-wide association study of plasma levels... \n",
"266 Genome-wide association study of plasma levels... \n",
"267 Genome-wide association study of plasma levels... \n",
"... ... \n",
"104237 Genetic analysis of over 1 million people iden... \n",
"104324 Genetic analysis of over 1 million people iden... \n",
"104325 Genetic analysis of over 1 million people iden... \n",
"104330 Genetic analysis of over 1 million people iden... \n",
"104337 Genetic analysis of over 1 million people iden... \n",
"104347 Genetic analysis of over 1 million people iden... \n",
"104356 Genetic analysis of over 1 million people iden... \n",
"104365 Genetic analysis of over 1 million people iden... \n",
"104376 Genetic analysis of over 1 million people iden... \n",
"104386 Genetic analysis of over 1 million people iden... \n",
"104387 Genetic analysis of over 1 million people iden... \n",
"104391 Genetic analysis of over 1 million people iden... \n",
"104394 Genetic analysis of over 1 million people iden... \n",
"104399 Genetic analysis of over 1 million people iden... \n",
"104401 Genetic analysis of over 1 million people iden... \n",
"104402 Genetic analysis of over 1 million people iden... \n",
"104405 Genetic analysis of over 1 million people iden... \n",
"104406 Genetic analysis of over 1 million people iden... \n",
"104412 Genetic analysis of over 1 million people iden... \n",
"104413 Genetic analysis of over 1 million people iden... \n",
"104415 Genetic analysis of over 1 million people iden... \n",
"104425 Genetic analysis of over 1 million people iden... \n",
"104429 Genetic analysis of over 1 million people iden... \n",
"104442 Genetic analysis of over 1 million people iden... \n",
"104448 Genetic analysis of over 1 million people iden... \n",
"104461 Genetic analysis of over 1 million people iden... \n",
"104466 Genetic analysis of over 1 million people iden... \n",
"104468 Genetic analysis of over 1 million people iden... \n",
"104469 Genetic analysis of over 1 million people iden... \n",
"104478 Genetic analysis of over 1 million people iden... \n",
"\n",
" DISEASE/TRAIT \\\n",
"0 Inflammatory skin disease \n",
"1 Inflammatory skin disease \n",
"5 Inflammatory skin disease \n",
"20 Inflammatory skin disease \n",
"24 Inflammatory skin disease \n",
"31 Inflammatory skin disease \n",
"38 Inflammatory skin disease \n",
"42 Inflammatory skin disease \n",
"47 Inflammatory skin disease \n",
"57 Inflammatory skin disease \n",
"128 Epithelial ovarian cancer \n",
"129 Epithelial ovarian cancer \n",
"164 Information processing speed \n",
"166 Serum alpha1-antitrypsin levels \n",
"170 Acute kidney injury in coronary artery bypass ... \n",
"174 Bone mineral accretion in asthma (oral cortico... \n",
"182 Noise-induced hearing loss \n",
"191 Colorectal cancer \n",
"192 Colorectal cancer \n",
"211 Milk allergy \n",
"217 Food allergy \n",
"223 Egg allergy \n",
"231 Myeloproliferative neoplasms \n",
"242 Lead levels in blood \n",
"243 Lead levels in blood \n",
"244 Lead levels in blood \n",
"260 Polychlorinated biphenyl levels \n",
"262 Polychlorinated biphenyl levels \n",
"266 Polychlorinated biphenyl levels \n",
"267 Polychlorinated biphenyl levels \n",
"... ... \n",
"104237 Pulse pressure \n",
"104324 Systolic blood pressure \n",
"104325 Systolic blood pressure \n",
"104330 Systolic blood pressure \n",
"104337 Systolic blood pressure \n",
"104347 Systolic blood pressure \n",
"104356 Systolic blood pressure \n",
"104365 Systolic blood pressure \n",
"104376 Systolic blood pressure \n",
"104386 Diastolic blood pressure \n",
"104387 Diastolic blood pressure \n",
"104391 Diastolic blood pressure \n",
"104394 Diastolic blood pressure \n",
"104399 Diastolic blood pressure \n",
"104401 Diastolic blood pressure \n",
"104402 Diastolic blood pressure \n",
"104405 Diastolic blood pressure \n",
"104406 Diastolic blood pressure \n",
"104412 Diastolic blood pressure \n",
"104413 Diastolic blood pressure \n",
"104415 Diastolic blood pressure \n",
"104425 Diastolic blood pressure \n",
"104429 Diastolic blood pressure \n",
"104442 Diastolic blood pressure \n",
"104448 Diastolic blood pressure \n",
"104461 Diastolic blood pressure \n",
"104466 Diastolic blood pressure \n",
"104468 Diastolic blood pressure \n",
"104469 Diastolic blood pressure \n",
"104478 Diastolic blood pressure \n",
"\n",
" INITIAL SAMPLE SIZE \\\n",
"0 2,079 European ancestry atopic dermatitis case... \n",
"1 2,079 European ancestry atopic dermatitis case... \n",
"5 2,079 European ancestry atopic dermatitis case... \n",
"20 2,079 European ancestry atopic dermatitis case... \n",
"24 2,079 European ancestry atopic dermatitis case... \n",
"31 2,079 European ancestry atopic dermatitis case... \n",
"38 2,079 European ancestry atopic dermatitis case... \n",
"42 2,079 European ancestry atopic dermatitis case... \n",
"47 2,079 European ancestry atopic dermatitis case... \n",
"57 2,079 European ancestry atopic dermatitis case... \n",
"128 4,368 European ancestry cases, 9,123 European ... \n",
"129 4,368 European ancestry cases, 9,123 European ... \n",
"164 Up to 30,807 European ancestry individuals, up... \n",
"166 3,294 Japanese ancestry individuals \n",
"170 873 European ancestry cases \n",
"174 489 European ancestry children \n",
"182 19 European and Mexican ancestry exposed indiv... \n",
"191 18,299 European ancestry cases, 19,656 Europea... \n",
"192 18,299 European ancestry cases, 19,656 Europea... \n",
"211 291 European ancestry child cases, 144 Europea... \n",
"217 671 European ancestry child cases, 144 Europea... \n",
"223 217 European ancestry child cases, 144 Europea... \n",
"231 524 European ancestry JAK2 negative cases, 2,6... \n",
"242 5,433 individuals \n",
"243 5,433 individuals \n",
"244 5,433 individuals \n",
"260 922 European ancestry individuals \n",
"262 922 European ancestry individuals \n",
"266 922 European ancestry individuals \n",
"267 922 European ancestry individuals \n",
"... ... \n",
"104237 757,601 European ancestry individuals \n",
"104324 757,601 European ancestry individuals \n",
"104325 757,601 European ancestry individuals \n",
"104330 757,601 European ancestry individuals \n",
"104337 757,601 European ancestry individuals \n",
"104347 757,601 European ancestry individuals \n",
"104356 757,601 European ancestry individuals \n",
"104365 757,601 European ancestry individuals \n",
"104376 757,601 European ancestry individuals \n",
"104386 757,601 European ancestry individuals \n",
"104387 757,601 European ancestry individuals \n",
"104391 757,601 European ancestry individuals \n",
"104394 757,601 European ancestry individuals \n",
"104399 757,601 European ancestry individuals \n",
"104401 757,601 European ancestry individuals \n",
"104402 757,601 European ancestry individuals \n",
"104405 757,601 European ancestry individuals \n",
"104406 757,601 European ancestry individuals \n",
"104412 757,601 European ancestry individuals \n",
"104413 757,601 European ancestry individuals \n",
"104415 757,601 European ancestry individuals \n",
"104425 757,601 European ancestry individuals \n",
"104429 757,601 European ancestry individuals \n",
"104442 757,601 European ancestry individuals \n",
"104448 757,601 European ancestry individuals \n",
"104461 757,601 European ancestry individuals \n",
"104466 757,601 European ancestry individuals \n",
"104468 757,601 European ancestry individuals \n",
"104469 757,601 European ancestry individuals \n",
"104478 757,601 European ancestry individuals \n",
"\n",
" REPLICATION SAMPLE SIZE ... P-VALUE \\\n",
"0 NaN ... 4e-08 \n",
"1 NaN ... 6e-08 \n",
"5 NaN ... 4e-12 \n",
"20 NaN ... 2e-12 \n",
"24 NaN ... 4e-11 \n",
"31 NaN ... 4e-10 \n",
"38 NaN ... 3e-08 \n",
"42 NaN ... 6e-08 \n",
"47 NaN ... 5e-07 \n",
"57 NaN ... 7e-09 \n",
"128 2,462 European ancestry BRCA1 mutation carrier... ... 9e-14 \n",
"129 2,462 European ancestry BRCA1 mutation carrier... ... 6e-51 \n",
"164 Up to 8,436 European ancestry individuals, up ... ... 3e-09 \n",
"166 6,065 Japanese ancestry individuals ... 3e-16 \n",
"170 380 European ancestry cases ... 5e-07 \n",
"174 NaN ... 4e-08 \n",
"182 NaN ... 5e-07 \n",
"191 4,725 East Asian ancestry cases, 9,969 East As... ... 3e-09 \n",
"192 4,725 East Asian ancestry cases, 9,969 East As... ... 2e-08 \n",
"211 NaN ... 2e-06 \n",
"217 NaN ... 5e-06 \n",
"223 NaN ... 4e-06 \n",
"231 1,383 European ancestry JAK2 negative cases, 4... ... 2e-09 \n",
"242 NaN ... 4e-06 \n",
"243 NaN ... 1e-06 \n",
"244 NaN ... 2e-06 \n",
"260 NaN ... 3e-08 \n",
"262 NaN ... 2e-07 \n",
"266 NaN ... 6e-07 \n",
"267 NaN ... 5e-07 \n",
"... ... ... ... \n",
"104237 249,262 European ancestry individuals ... 2e-08 \n",
"104324 NaN ... 8e-15 \n",
"104325 NaN ... 1e-14 \n",
"104330 NaN ... 2e-12 \n",
"104337 NaN ... 2e-11 \n",
"104347 NaN ... 1e-10 \n",
"104356 NaN ... 4e-10 \n",
"104365 NaN ... 6e-10 \n",
"104376 NaN ... 5e-09 \n",
"104386 NaN ... 7e-15 \n",
"104387 NaN ... 2e-14 \n",
"104391 NaN ... 2e-13 \n",
"104394 NaN ... 2e-12 \n",
"104399 NaN ... 3e-12 \n",
"104401 NaN ... 4e-12 \n",
"104402 NaN ... 5e-12 \n",
"104405 NaN ... 8e-12 \n",
"104406 NaN ... 1e-11 \n",
"104412 NaN ... 2e-11 \n",
"104413 NaN ... 2e-11 \n",
"104415 NaN ... 3e-11 \n",
"104425 NaN ... 8e-11 \n",
"104429 NaN ... 1e-10 \n",
"104442 NaN ... 4e-10 \n",
"104448 NaN ... 6e-10 \n",
"104461 NaN ... 2e-09 \n",
"104466 NaN ... 3e-09 \n",
"104468 NaN ... 4e-09 \n",
"104469 NaN ... 4e-09 \n",
"104478 NaN ... 5e-09 \n",
"\n",
" PVALUE_MLOG P-VALUE (TEXT) OR or BETA \\\n",
"0 7.397940 (Opposed) NaN \n",
"1 7.221849 (Opposed) NaN \n",
"5 11.397940 (Psoriasis) 1.2000 \n",
"20 11.698970 (Psoriasis) NaN \n",
"24 10.397940 (Psoriasis) NaN \n",
"31 9.397940 (Psoriasis) NaN \n",
"38 7.522879 (Psoriasis) NaN \n",
"42 7.221849 (Psoriasis) NaN \n",
"47 6.301030 (Psoriasis) NaN \n",
"57 8.154902 (Shared) NaN \n",
"128 13.045757 NaN 1.1400 \n",
"129 50.221849 NaN 1.5900 \n",
"164 8.522879 (LDST/DSST- age, sex, and education adjusted) 5.9200 \n",
"166 15.522879 NaN 2.0500 \n",
"170 6.301030 NaN 21.6600 \n",
"174 7.397940 NaN NaN \n",
"182 6.301030 NaN 12.7500 \n",
"191 8.522879 NaN 1.1400 \n",
"192 7.698970 NaN 1.0900 \n",
"211 5.698970 NaN NaN \n",
"217 5.301030 NaN NaN \n",
"223 5.397940 NaN NaN \n",
"231 8.698970 NaN 1.2200 \n",
"242 5.397940 NaN 0.1950 \n",
"243 6.000000 NaN 0.1940 \n",
"244 5.698970 NaN 0.2760 \n",
"260 7.522879 (PCB126) 1.2300 \n",
"262 6.698970 (PCB138) 1.1100 \n",
"266 6.221849 (PCB153) 1.0200 \n",
"267 6.301030 (PCB153) 0.7600 \n",
"... ... ... ... \n",
"104237 7.698970 NaN 0.1154 \n",
"104324 14.096910 NaN 0.2371 \n",
"104325 14.000000 NaN 0.2528 \n",
"104330 11.698970 NaN 0.2161 \n",
"104337 10.698970 NaN 0.2092 \n",
"104347 10.000000 NaN 0.3358 \n",
"104356 9.397940 NaN 0.1893 \n",
"104365 9.221849 NaN 0.1909 \n",
"104376 8.301030 NaN 0.1824 \n",
"104386 14.154902 NaN 0.1645 \n",
"104387 13.698970 NaN 0.1801 \n",
"104391 12.698970 NaN 0.1398 \n",
"104394 11.698970 NaN 0.1576 \n",
"104399 11.522879 NaN 0.1279 \n",
"104401 11.397940 NaN 0.1229 \n",
"104402 11.301030 NaN 0.1207 \n",
"104405 11.096910 NaN 0.1225 \n",
"104406 11.000000 NaN 0.1271 \n",
"104412 10.698970 NaN 0.1211 \n",
"104413 10.698970 NaN 0.1176 \n",
"104415 10.522879 NaN 0.1171 \n",
"104425 10.096910 NaN 0.1444 \n",
"104429 10.000000 NaN 0.1470 \n",
"104442 9.397940 NaN 0.1142 \n",
"104448 9.221849 NaN 0.1325 \n",
"104461 8.698970 NaN 0.1962 \n",
"104466 8.522879 NaN 0.1391 \n",
"104468 8.397940 NaN 0.1244 \n",
"104469 8.397940 NaN 0.1364 \n",
"104478 8.301030 NaN 0.1394 \n",
"\n",
" 95% CI (TEXT) \\\n",
"0 NaN \n",
"1 NaN \n",
"5 [1.15–1.27] \n",
"20 NaN \n",
"24 NaN \n",
"31 NaN \n",
"38 NaN \n",
"42 NaN \n",
"47 NaN \n",
"57 NaN \n",
"128 [1.10-1.19] \n",
"129 [1.48-1.70] \n",
"164 [NR] unit increase \n",
"166 [1.56-2.54] mg dl-1 increase \n",
"170 [13.19-30.13] unit increase \n",
"174 NaN \n",
"182 [NR] \n",
"191 [1.09-1.19] \n",
"192 [1.05-1.11] \n",
"211 NaN \n",
"217 NaN \n",
"223 NaN \n",
"231 [1.14-1.30] \n",
"242 [0.077-0.313] unit decrease \n",
"243 [0.11-0.28] unit increase \n",
"244 [0.11-0.45] unit increase \n",
"260 [0.8-1.66] unit decrease \n",
"262 [0.7-1.52] unit decrease \n",
"266 [0.63-1.41] unit decrease \n",
"267 [0.47-1.05] unit decrease \n",
"... ... \n",
"104237 [0.075-0.156] unit decrease \n",
"104324 [0.18-0.3] mmHg increase \n",
"104325 [0.19-0.32] mmHg increase \n",
"104330 [0.16-0.28] mmHg increase \n",
"104337 [0.15-0.27] mmHg increase \n",
"104347 [0.23-0.44] mmHg increase \n",
"104356 [0.13-0.25] mmHg increase \n",
"104365 [0.13-0.25] mmHg decrease \n",
"104376 [0.12-0.24] mmHg increase \n",
"104386 [0.12-0.21] mmHg increase \n",
"104387 [0.13-0.23] mmHg decrease \n",
"104391 [0.1-0.18] mmHg decrease \n",
"104394 [0.11-0.2] mmHg increase \n",
"104399 [0.092-0.164] mmHg increase \n",
"104401 [0.088-0.158] mmHg increase \n",
"104402 [0.086-0.155] mmHg increase \n",
"104405 [0.087-0.158] mmHg increase \n",
"104406 [0.09-0.164] mmHg decrease \n",
"104412 [0.086-0.156] mmHg increase \n",
"104413 [0.083-0.152] mmHg decrease \n",
"104415 [0.083-0.152] mmHg increase \n",
"104425 [0.1-0.19] mmHg increase \n",
"104429 [0.1-0.19] mmHg decrease \n",
"104442 [0.079-0.15] mmHg decrease \n",
"104448 [0.091-0.174] mmHg decrease \n",
"104461 [0.13-0.26] mmHg decrease \n",
"104466 [0.093-0.185] mmHg increase \n",
"104468 [0.083-0.166] mmHg decrease \n",
"104469 [0.091-0.182] mmHg increase \n",
"104478 [0.093-0.186] mmHg decrease \n",
"\n",
" PLATFORM [SNPS PASSING QC] CNV my_index x \\\n",
"0 Affymetrix, Illumina [~ 5200000] N 0 0 \n",
"1 Affymetrix, Illumina [~ 5200000] N 1 1 \n",
"5 Affymetrix, Illumina [~ 5200000] N 5 5 \n",
"20 Affymetrix, Illumina [~ 5200000] N 20 20 \n",
"24 Affymetrix, Illumina [~ 5200000] N 24 24 \n",
"31 Affymetrix, Illumina [~ 5200000] N 31 31 \n",
"38 Affymetrix, Illumina [~ 5200000] N 38 38 \n",
"42 Affymetrix, Illumina [~ 5200000] N 42 42 \n",
"47 Affymetrix, Illumina [~ 5200000] N 47 47 \n",
"57 Affymetrix, Illumina [~ 5200000] N 57 57 \n",
"128 Illumina [up to 10962898] (imputed) N 128 128 \n",
"129 Illumina [up to 10962898] (imputed) N 129 129 \n",
"164 Affymetrix, Illumina [up to 2357391] (imputed) N 164 164 \n",
"166 Illumina [6569727] (imputed) N 166 166 \n",
"170 Illumina [530716] (imputed) N 170 170 \n",
"174 Illumina [NR] N 174 174 \n",
"182 Affymetrix [289036] N 182 182 \n",
"191 Affymetrix, Illumina [~ 2500000] (imputed) N 191 191 \n",
"192 Affymetrix, Illumina [~ 2500000] (imputed) N 192 192 \n",
"211 Illumina [6459842] (imputed) N 211 211 \n",
"217 Illumina [6459842] (imputed) N 217 217 \n",
"223 Illumina [6459842] (imputed) N 223 223 \n",
"231 Affymetrix [2098039] (imputed) N 231 231 \n",
"242 Illumina [6391392] (imputed) N 242 242 \n",
"243 Illumina [6391392] (imputed) N 243 243 \n",
"244 Illumina [6391392] (imputed) N 244 244 \n",
"260 Illumina [8736858] (imputed) N 260 260 \n",
"262 Illumina [8736858] (imputed) N 262 262 \n",
"266 Illumina [8736858] (imputed) N 266 266 \n",
"267 Illumina [8736858] (imputed) N 267 267 \n",
"... ... ... ... ... \n",
"104237 Affymetrix, Illumina [~ 7100000] (imputed) N 104237 104237 \n",
"104324 Affymetrix, Illumina [~ 7100000] (imputed) N 104324 104324 \n",
"104325 Affymetrix, Illumina [~ 7100000] (imputed) N 104325 104325 \n",
"104330 Affymetrix, Illumina [~ 7100000] (imputed) N 104330 104330 \n",
"104337 Affymetrix, Illumina [~ 7100000] (imputed) N 104337 104337 \n",
"104347 Affymetrix, Illumina [~ 7100000] (imputed) N 104347 104347 \n",
"104356 Affymetrix, Illumina [~ 7100000] (imputed) N 104356 104356 \n",
"104365 Affymetrix, Illumina [~ 7100000] (imputed) N 104365 104365 \n",
"104376 Affymetrix, Illumina [~ 7100000] (imputed) N 104376 104376 \n",
"104386 Affymetrix, Illumina [~ 7100000] (imputed) N 104386 104386 \n",
"104387 Affymetrix, Illumina [~ 7100000] (imputed) N 104387 104387 \n",
"104391 Affymetrix, Illumina [~ 7100000] (imputed) N 104391 104391 \n",
"104394 Affymetrix, Illumina [~ 7100000] (imputed) N 104394 104394 \n",
"104399 Affymetrix, Illumina [~ 7100000] (imputed) N 104399 104399 \n",
"104401 Affymetrix, Illumina [~ 7100000] (imputed) N 104401 104401 \n",
"104402 Affymetrix, Illumina [~ 7100000] (imputed) N 104402 104402 \n",
"104405 Affymetrix, Illumina [~ 7100000] (imputed) N 104405 104405 \n",
"104406 Affymetrix, Illumina [~ 7100000] (imputed) N 104406 104406 \n",
"104412 Affymetrix, Illumina [~ 7100000] (imputed) N 104412 104412 \n",
"104413 Affymetrix, Illumina [~ 7100000] (imputed) N 104413 104413 \n",
"104415 Affymetrix, Illumina [~ 7100000] (imputed) N 104415 104415 \n",
"104425 Affymetrix, Illumina [~ 7100000] (imputed) N 104425 104425 \n",
"104429 Affymetrix, Illumina [~ 7100000] (imputed) N 104429 104429 \n",
"104442 Affymetrix, Illumina [~ 7100000] (imputed) N 104442 104442 \n",
"104448 Affymetrix, Illumina [~ 7100000] (imputed) N 104448 104448 \n",
"104461 Affymetrix, Illumina [~ 7100000] (imputed) N 104461 104461 \n",
"104466 Affymetrix, Illumina [~ 7100000] (imputed) N 104466 104466 \n",
"104468 Affymetrix, Illumina [~ 7100000] (imputed) N 104468 104468 \n",
"104469 Affymetrix, Illumina [~ 7100000] (imputed) N 104469 104469 \n",
"104478 Affymetrix, Illumina [~ 7100000] (imputed) N 104478 104478 \n",
"\n",
" y \n",
"0 2015-01-08 \n",
"1 2015-01-08 \n",
"5 2015-01-08 \n",
"20 2015-01-08 \n",
"24 2015-01-08 \n",
"31 2015-01-08 \n",
"38 2015-01-08 \n",
"42 2015-01-08 \n",
"47 2015-01-08 \n",
"57 2015-01-08 \n",
"128 2015-01-12 \n",
"129 2015-01-12 \n",
"164 2015-04-14 \n",
"166 2015-07-15 \n",
"170 2015-06-17 \n",
"174 2015-05-27 \n",
"182 2015-06-29 \n",
"191 2015-07-07 \n",
"192 2015-07-07 \n",
"211 2015-02-24 \n",
"217 2015-02-24 \n",
"223 2015-02-24 \n",
"231 2015-04-07 \n",
"242 2015-03-27 \n",
"243 2015-03-27 \n",
"244 2015-03-27 \n",
"260 2015-04-02 \n",
"262 2015-04-02 \n",
"266 2015-04-02 \n",
"267 2015-04-02 \n",
"... ... \n",
"104237 2018-09-17 \n",
"104324 2018-09-17 \n",
"104325 2018-09-17 \n",
"104330 2018-09-17 \n",
"104337 2018-09-17 \n",
"104347 2018-09-17 \n",
"104356 2018-09-17 \n",
"104365 2018-09-17 \n",
"104376 2018-09-17 \n",
"104386 2018-09-17 \n",
"104387 2018-09-17 \n",
"104391 2018-09-17 \n",
"104394 2018-09-17 \n",
"104399 2018-09-17 \n",
"104401 2018-09-17 \n",
"104402 2018-09-17 \n",
"104405 2018-09-17 \n",
"104406 2018-09-17 \n",
"104412 2018-09-17 \n",
"104413 2018-09-17 \n",
"104415 2018-09-17 \n",
"104425 2018-09-17 \n",
"104429 2018-09-17 \n",
"104442 2018-09-17 \n",
"104448 2018-09-17 \n",
"104461 2018-09-17 \n",
"104466 2018-09-17 \n",
"104468 2018-09-17 \n",
"104469 2018-09-17 \n",
"104478 2018-09-17 \n",
"\n",
"[14812 rows x 37 columns]"
]
},
"execution_count": 123,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[gwas['CHR_ID'].isin(['2', '3'])]"
]
},
{
"cell_type": "code",
"execution_count": 125,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['3', '2', '17', '10', '1', '6', '5', '12', '20', '18', '19', '9',\n",
" '7', '14', '8', '11', '4', '21', '15', '13', '16', nan, 'X', '22',\n",
" '6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6;6',\n",
" '10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10;10',\n",
" 'Y', '5 x 6', '9;9', '1;1;1;1;1;1;1;1;1;1;1;1;1;1;1;1', '20;20',\n",
" '12;12;12', '10;10;10', '20;20;20;20', '9;9;9;9', '19;19;19;19',\n",
" '2;2;2;2', '22;22;22;22', '1;1;1;1', '11;11;11;11', '7;7;7;7',\n",
" '10;10;10;10', '4;4;4;4', '3;3;3;3', '6;6;6;6', '8;8;8', '1;1',\n",
" '2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2;2', '6;6;6', '15;15', '4;4',\n",
" '17;17;17;17;17;17;17;17;17;17;17;17', '17;17;17;17;17;17;17',\n",
" '16;16;16', '16;16;16;16;16;16', '12;12', '6;6;6;6;6', '1 x 7',\n",
" '2 x 6', '1 x 9', '6 x 16', '9 x 10', '1 x 6', '6 x 8', '3 x 3',\n",
" '4 x 6', '10 x 12', '3 x 18', '5 x 8', '13 x 18', '7 x 15',\n",
" '3 x 5', '2 x 5', '5 x 16', '2 x 15', '10 x 14', '5 x 17',\n",
" '7 x 16', '1 x 13', '6 x 7', '3 x 11', '1 x 14', '4 x 22', '9 x 9',\n",
" '5 x 11', '10 x 22', '5 x 7', '6 x 12', '8 x 10', '5 x 14',\n",
" '3 x 7', '14 x 21', '10 x 11', '1 x 3', '2 x 3', '2 x 12',\n",
" '4 x 11', '2 x 9', '8 x 15', '12 x 20', '5 x 10', '9 x 15',\n",
" '6 x 1', '7 x 1', '4 x 12', '3 x 20', '8 x 9', '10 x 19',\n",
" '12 x 17', '7 x 10', '14 x 11', '9 x 4', '9 x 8', '6 x 17',\n",
" '2 x 17', '20 x 19', '7 x 8', '5 x 3', '5 x 19', '14 x 3',\n",
" '22 x 11', '8 x 11', '4 x 8', '15 x 8', '3 x 10', '4 x 19',\n",
" '12 x 22', '3 x 2', '13 x 8', '15 x 11', '18 x 3', '2 x 11',\n",
" '10 x 8', '12 x 8', '7 x 17', '9 x 3', '3 x 22', '13 x 2',\n",
" '22 x 8', '22 x 4', '18 x X', '11 x 4', '1 x 17', '16 x 7',\n",
" '3 x 4', '6 x 6', '1 x 19', '8;8', '2;2;2', '3;3', '8 x 18',\n",
" '4 x 20', '10 x 21', '13 x 16', '12 x 15', '5 x 13', '1 x 16',\n",
" '7 x 20', '2 x 13', '1 x 10', '7 x 9', '5 x 15', '6 x 9', '13 x 5',\n",
" '3 x 9', '3 x 15', '18 x 22', '5 x 21', '3 x 12', '2 x 20',\n",
" '12 x 16', '4 x 18', '6;6;6;6;6;6', '1;1;1', '1;1;1;1;1;1',\n",
" '1;1;1;1;1;1;1', '1;1;1;1;1;1;1;1', '1;1;1;1;1;1;1;1;1', '5;5',\n",
" '17;17', '1;1;1;1;1', '4;4;4;4;4', '2;2;2;2;2;2;2;2;2;2;2;2',\n",
" '14;14;14;14;14;14', '2;1;2;2;2;2;2;2;2;2;2;2;2;2', '2;2', '7;7',\n",
" '11;11;11', '8;8;8;8;8;8;8;8;8;8;8;8;8;8', '19;19;19;19;19;19;19',\n",
" '2 x 2', '5 x 5', '8 x 8', '12 x 12', '20 x 20', '1 x 1', '4 x 4',\n",
" '6;6', '1;1;1;1;1;1;1;1;1;1',\n",
" '7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7;7',\n",
" '11;11;11;11;11;11;11;11;11;11', '14;14;14;14;14;14;14;14;14;14',\n",
" '16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16;16',\n",
" '17;17;17;17;17;17;17;17;17;17',\n",
" '21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21;21',\n",
" '10;10', '11;11', '13;13', '18;18', '5;5;5;5;5;5;5;5;5', '15 x 6',\n",
" '15 x 18', '15 x 5', '15 x 12', '15 x 9', '15 x 20', '15 x 1',\n",
" '15 x 2', '15 x 3', '11 x 2', '11 x 16', '11 x 18', '11 x 8',\n",
" '11 x 21', '11 x 22', '11 x 12', '11 x 13', '11 x 19', '11 x 1',\n",
" '11 x 3', '11 x 20', '11 x 10', '4 x 10', '2 x 21', '7 x 7',\n",
" '9 x 16', '10 x 6', '10 x 13', '13 x 13', '1 x 18', '4 x 13',\n",
" '1 x 5', '13 x 17', '4 x 15', '6 x 21', '6 x 22', '1 x 2',\n",
" '12 x 21', '7 x 19', '4 x 17', '10 x 20'], dtype=object)"
]
},
"execution_count": 125,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas['CHR_ID'].unique()"
]
},
{
"cell_type": "code",
"execution_count": 129,
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>DATE ADDED TO CATALOG</th>\n",
" <th>PUBMEDID</th>\n",
" <th>FIRST AUTHOR</th>\n",
" <th>DATE</th>\n",
" <th>JOURNAL</th>\n",
" <th>LINK</th>\n",
" <th>STUDY</th>\n",
" <th>DISEASE/TRAIT</th>\n",
" <th>INITIAL SAMPLE SIZE</th>\n",
" <th>REPLICATION SAMPLE SIZE</th>\n",
" <th>...</th>\n",
" <th>P-VALUE</th>\n",
" <th>PVALUE_MLOG</th>\n",
" <th>P-VALUE (TEXT)</th>\n",
" <th>OR or BETA</th>\n",
" <th>95% CI (TEXT)</th>\n",
" <th>PLATFORM [SNPS PASSING QC]</th>\n",
" <th>CNV</th>\n",
" <th>my_index</th>\n",
" <th>x</th>\n",
" <th>y</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-08</td>\n",
" <td>7.397940</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-08</td>\n",
" <td>7.221849</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-07</td>\n",
" <td>6.698970</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-07</td>\n",
" <td>6.221849</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-06</td>\n",
" <td>5.221849</td>\n",
" <td>(Opposed)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-12</td>\n",
" <td>11.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.2000</td>\n",
" <td>[1.15–1.27]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.2200</td>\n",
" <td>[1.15–1.30]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>9e-16</td>\n",
" <td>15.045757</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.2700</td>\n",
" <td>[1.20–1.34]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-16</td>\n",
" <td>16.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.2700</td>\n",
" <td>[1.20–1.35]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-14</td>\n",
" <td>13.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.2900</td>\n",
" <td>[1.21–1.38]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-35</td>\n",
" <td>34.522879</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.3900</td>\n",
" <td>[1.32–1.47]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-25</td>\n",
" <td>25.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.4500</td>\n",
" <td>[1.35–1.56]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.4700</td>\n",
" <td>[1.32–1.64]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>12</td>\n",
" <td>12</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-12</td>\n",
" <td>11.522879</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.4700</td>\n",
" <td>[1.33–1.67]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>13</td>\n",
" <td>13</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-26</td>\n",
" <td>26.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.5800</td>\n",
" <td>[1.45–1.72]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>14</td>\n",
" <td>14</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-18</td>\n",
" <td>17.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>15</td>\n",
" <td>15</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-17</td>\n",
" <td>16.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>16</td>\n",
" <td>16</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-16</td>\n",
" <td>15.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-14</td>\n",
" <td>13.522879</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>18</td>\n",
" <td>18</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-13</td>\n",
" <td>12.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>19</td>\n",
" <td>19</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-12</td>\n",
" <td>11.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>21</td>\n",
" <td>21</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-12</td>\n",
" <td>11.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>22</td>\n",
" <td>22</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-11</td>\n",
" <td>11.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>23</td>\n",
" <td>23</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-11</td>\n",
" <td>10.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>24</td>\n",
" <td>24</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-11</td>\n",
" <td>10.301030</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-11</td>\n",
" <td>10.301030</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>26</td>\n",
" <td>26</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-11</td>\n",
" <td>10.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>27</td>\n",
" <td>27</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-10</td>\n",
" <td>10.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>28</td>\n",
" <td>28</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-10</td>\n",
" <td>9.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>29</td>\n",
" <td>29</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104449</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-10</td>\n",
" <td>9.221849</td>\n",
" <td>NaN</td>\n",
" <td>0.1203</td>\n",
" <td>[0.082-0.159] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104449</td>\n",
" <td>104449</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104450</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>7e-10</td>\n",
" <td>9.154902</td>\n",
" <td>NaN</td>\n",
" <td>0.1150</td>\n",
" <td>[0.079-0.151] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104450</td>\n",
" <td>104450</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104451</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>7e-10</td>\n",
" <td>9.154902</td>\n",
" <td>NaN</td>\n",
" <td>0.1540</td>\n",
" <td>[0.1-0.2] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104451</td>\n",
" <td>104451</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104452</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>8e-10</td>\n",
" <td>9.096910</td>\n",
" <td>NaN</td>\n",
" <td>0.1071</td>\n",
" <td>[0.073-0.141] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104452</td>\n",
" <td>104452</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104453</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>8e-10</td>\n",
" <td>9.096910</td>\n",
" <td>NaN</td>\n",
" <td>0.1173</td>\n",
" <td>[0.08-0.155] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104453</td>\n",
" <td>104453</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104454</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>9e-10</td>\n",
" <td>9.045757</td>\n",
" <td>NaN</td>\n",
" <td>0.1242</td>\n",
" <td>[0.084-0.164] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104454</td>\n",
" <td>104454</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104455</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>9e-10</td>\n",
" <td>9.045757</td>\n",
" <td>NaN</td>\n",
" <td>0.1103</td>\n",
" <td>[0.075-0.146] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104455</td>\n",
" <td>104455</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104456</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-09</td>\n",
" <td>9.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1096</td>\n",
" <td>[0.075-0.145] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104456</td>\n",
" <td>104456</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104457</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-09</td>\n",
" <td>9.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1233</td>\n",
" <td>[0.084-0.163] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104457</td>\n",
" <td>104457</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104458</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-09</td>\n",
" <td>9.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1319</td>\n",
" <td>[0.09-0.174] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104458</td>\n",
" <td>104458</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104459</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-09</td>\n",
" <td>9.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1152</td>\n",
" <td>[0.078-0.152] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104459</td>\n",
" <td>104459</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104460</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-09</td>\n",
" <td>9.000000</td>\n",
" <td>NaN</td>\n",
" <td>0.1258</td>\n",
" <td>[0.085-0.166] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104460</td>\n",
" <td>104460</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104461</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-09</td>\n",
" <td>8.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1962</td>\n",
" <td>[0.13-0.26] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104461</td>\n",
" <td>104461</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104462</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-09</td>\n",
" <td>8.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.2140</td>\n",
" <td>[0.14-0.28] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104462</td>\n",
" <td>104462</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104463</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-09</td>\n",
" <td>8.698970</td>\n",
" <td>NaN</td>\n",
" <td>0.1878</td>\n",
" <td>[0.13-0.25] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104463</td>\n",
" <td>104463</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104464</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-09</td>\n",
" <td>8.522879</td>\n",
" <td>NaN</td>\n",
" <td>0.1036</td>\n",
" <td>[0.069-0.138] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104464</td>\n",
" <td>104464</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104465</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-09</td>\n",
" <td>8.522879</td>\n",
" <td>NaN</td>\n",
" <td>0.1511</td>\n",
" <td>[0.1-0.2] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104465</td>\n",
" <td>104465</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104466</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-09</td>\n",
" <td>8.522879</td>\n",
" <td>NaN</td>\n",
" <td>0.1391</td>\n",
" <td>[0.093-0.185] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104466</td>\n",
" <td>104466</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104467</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-09</td>\n",
" <td>8.522879</td>\n",
" <td>NaN</td>\n",
" <td>0.1400</td>\n",
" <td>[0.094-0.186] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104467</td>\n",
" <td>104467</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104468</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1244</td>\n",
" <td>[0.083-0.166] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104468</td>\n",
" <td>104468</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104469</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1364</td>\n",
" <td>[0.091-0.182] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104469</td>\n",
" <td>104469</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104470</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1124</td>\n",
" <td>[0.075-0.15] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104470</td>\n",
" <td>104470</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104471</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1054</td>\n",
" <td>[0.07-0.14] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104471</td>\n",
" <td>104471</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104472</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1478</td>\n",
" <td>[0.099-0.197] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104472</td>\n",
" <td>104472</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104473</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1760</td>\n",
" <td>[0.12-0.23] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104473</td>\n",
" <td>104473</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104474</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1692</td>\n",
" <td>[0.11-0.23] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104474</td>\n",
" <td>104474</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104475</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1294</td>\n",
" <td>[0.086-0.173] mmHg increase</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104475</td>\n",
" <td>104475</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104476</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>NaN</td>\n",
" <td>0.1082</td>\n",
" <td>[0.072-0.144] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104476</td>\n",
" <td>104476</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104477</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-09</td>\n",
" <td>8.301030</td>\n",
" <td>NaN</td>\n",
" <td>0.1072</td>\n",
" <td>[0.071-0.143] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104477</td>\n",
" <td>104477</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" <tr>\n",
" <th>104478</th>\n",
" <td>2018-11-29</td>\n",
" <td>30224653</td>\n",
" <td>Evangelou E</td>\n",
" <td>2018-09-17</td>\n",
" <td>Nat Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30224653</td>\n",
" <td>Genetic analysis of over 1 million people iden...</td>\n",
" <td>Diastolic blood pressure</td>\n",
" <td>757,601 European ancestry individuals</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-09</td>\n",
" <td>8.301030</td>\n",
" <td>NaN</td>\n",
" <td>0.1394</td>\n",
" <td>[0.093-0.186] mmHg decrease</td>\n",
" <td>Affymetrix, Illumina [~ 7100000] (imputed)</td>\n",
" <td>N</td>\n",
" <td>104478</td>\n",
" <td>104478</td>\n",
" <td>2018-09-17</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>101029 rows × 37 columns</p>\n",
"</div>"
],
"text/plain": [
" DATE ADDED TO CATALOG PUBMEDID FIRST AUTHOR DATE \\\n",
"0 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"1 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"2 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"3 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"4 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"5 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"6 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"7 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"8 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"9 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"10 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"11 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"12 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"13 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"14 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"15 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"16 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"17 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"18 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"19 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"20 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"21 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"22 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"23 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"24 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"25 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"26 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"27 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"28 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"29 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"... ... ... ... ... \n",
"104449 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104450 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104451 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104452 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104453 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104454 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104455 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104456 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104457 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104458 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104459 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104460 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104461 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104462 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104463 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104464 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104465 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104466 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104467 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104468 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104469 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104470 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104471 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104472 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104473 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104474 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104475 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104476 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104477 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"104478 2018-11-29 30224653 Evangelou E 2018-09-17 \n",
"\n",
" JOURNAL LINK \\\n",
"0 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"1 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"2 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"3 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"4 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"5 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"6 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"7 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"8 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"9 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"10 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"11 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"12 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"13 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"14 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"15 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"16 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"17 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"18 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"19 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"20 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"21 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"22 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"23 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"24 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"25 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"26 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"27 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"28 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"29 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"... ... ... \n",
"104449 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104450 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104451 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104452 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104453 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104454 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104455 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104456 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104457 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104458 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104459 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104460 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104461 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104462 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104463 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104464 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104465 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104466 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104467 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104468 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104469 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104470 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104471 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104472 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104473 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104474 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104475 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104476 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104477 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"104478 Nat Genet www.ncbi.nlm.nih.gov/pubmed/30224653 \n",
"\n",
" STUDY \\\n",
"0 Genome-wide comparative analysis of atopic der... \n",
"1 Genome-wide comparative analysis of atopic der... \n",
"2 Genome-wide comparative analysis of atopic der... \n",
"3 Genome-wide comparative analysis of atopic der... \n",
"4 Genome-wide comparative analysis of atopic der... \n",
"5 Genome-wide comparative analysis of atopic der... \n",
"6 Genome-wide comparative analysis of atopic der... \n",
"7 Genome-wide comparative analysis of atopic der... \n",
"8 Genome-wide comparative analysis of atopic der... \n",
"9 Genome-wide comparative analysis of atopic der... \n",
"10 Genome-wide comparative analysis of atopic der... \n",
"11 Genome-wide comparative analysis of atopic der... \n",
"12 Genome-wide comparative analysis of atopic der... \n",
"13 Genome-wide comparative analysis of atopic der... \n",
"14 Genome-wide comparative analysis of atopic der... \n",
"15 Genome-wide comparative analysis of atopic der... \n",
"16 Genome-wide comparative analysis of atopic der... \n",
"17 Genome-wide comparative analysis of atopic der... \n",
"18 Genome-wide comparative analysis of atopic der... \n",
"19 Genome-wide comparative analysis of atopic der... \n",
"20 Genome-wide comparative analysis of atopic der... \n",
"21 Genome-wide comparative analysis of atopic der... \n",
"22 Genome-wide comparative analysis of atopic der... \n",
"23 Genome-wide comparative analysis of atopic der... \n",
"24 Genome-wide comparative analysis of atopic der... \n",
"25 Genome-wide comparative analysis of atopic der... \n",
"26 Genome-wide comparative analysis of atopic der... \n",
"27 Genome-wide comparative analysis of atopic der... \n",
"28 Genome-wide comparative analysis of atopic der... \n",
"29 Genome-wide comparative analysis of atopic der... \n",
"... ... \n",
"104449 Genetic analysis of over 1 million people iden... \n",
"104450 Genetic analysis of over 1 million people iden... \n",
"104451 Genetic analysis of over 1 million people iden... \n",
"104452 Genetic analysis of over 1 million people iden... \n",
"104453 Genetic analysis of over 1 million people iden... \n",
"104454 Genetic analysis of over 1 million people iden... \n",
"104455 Genetic analysis of over 1 million people iden... \n",
"104456 Genetic analysis of over 1 million people iden... \n",
"104457 Genetic analysis of over 1 million people iden... \n",
"104458 Genetic analysis of over 1 million people iden... \n",
"104459 Genetic analysis of over 1 million people iden... \n",
"104460 Genetic analysis of over 1 million people iden... \n",
"104461 Genetic analysis of over 1 million people iden... \n",
"104462 Genetic analysis of over 1 million people iden... \n",
"104463 Genetic analysis of over 1 million people iden... \n",
"104464 Genetic analysis of over 1 million people iden... \n",
"104465 Genetic analysis of over 1 million people iden... \n",
"104466 Genetic analysis of over 1 million people iden... \n",
"104467 Genetic analysis of over 1 million people iden... \n",
"104468 Genetic analysis of over 1 million people iden... \n",
"104469 Genetic analysis of over 1 million people iden... \n",
"104470 Genetic analysis of over 1 million people iden... \n",
"104471 Genetic analysis of over 1 million people iden... \n",
"104472 Genetic analysis of over 1 million people iden... \n",
"104473 Genetic analysis of over 1 million people iden... \n",
"104474 Genetic analysis of over 1 million people iden... \n",
"104475 Genetic analysis of over 1 million people iden... \n",
"104476 Genetic analysis of over 1 million people iden... \n",
"104477 Genetic analysis of over 1 million people iden... \n",
"104478 Genetic analysis of over 1 million people iden... \n",
"\n",
" DISEASE/TRAIT \\\n",
"0 Inflammatory skin disease \n",
"1 Inflammatory skin disease \n",
"2 Inflammatory skin disease \n",
"3 Inflammatory skin disease \n",
"4 Inflammatory skin disease \n",
"5 Inflammatory skin disease \n",
"6 Inflammatory skin disease \n",
"7 Inflammatory skin disease \n",
"8 Inflammatory skin disease \n",
"9 Inflammatory skin disease \n",
"10 Inflammatory skin disease \n",
"11 Inflammatory skin disease \n",
"12 Inflammatory skin disease \n",
"13 Inflammatory skin disease \n",
"14 Inflammatory skin disease \n",
"15 Inflammatory skin disease \n",
"16 Inflammatory skin disease \n",
"17 Inflammatory skin disease \n",
"18 Inflammatory skin disease \n",
"19 Inflammatory skin disease \n",
"20 Inflammatory skin disease \n",
"21 Inflammatory skin disease \n",
"22 Inflammatory skin disease \n",
"23 Inflammatory skin disease \n",
"24 Inflammatory skin disease \n",
"25 Inflammatory skin disease \n",
"26 Inflammatory skin disease \n",
"27 Inflammatory skin disease \n",
"28 Inflammatory skin disease \n",
"29 Inflammatory skin disease \n",
"... ... \n",
"104449 Diastolic blood pressure \n",
"104450 Diastolic blood pressure \n",
"104451 Diastolic blood pressure \n",
"104452 Diastolic blood pressure \n",
"104453 Diastolic blood pressure \n",
"104454 Diastolic blood pressure \n",
"104455 Diastolic blood pressure \n",
"104456 Diastolic blood pressure \n",
"104457 Diastolic blood pressure \n",
"104458 Diastolic blood pressure \n",
"104459 Diastolic blood pressure \n",
"104460 Diastolic blood pressure \n",
"104461 Diastolic blood pressure \n",
"104462 Diastolic blood pressure \n",
"104463 Diastolic blood pressure \n",
"104464 Diastolic blood pressure \n",
"104465 Diastolic blood pressure \n",
"104466 Diastolic blood pressure \n",
"104467 Diastolic blood pressure \n",
"104468 Diastolic blood pressure \n",
"104469 Diastolic blood pressure \n",
"104470 Diastolic blood pressure \n",
"104471 Diastolic blood pressure \n",
"104472 Diastolic blood pressure \n",
"104473 Diastolic blood pressure \n",
"104474 Diastolic blood pressure \n",
"104475 Diastolic blood pressure \n",
"104476 Diastolic blood pressure \n",
"104477 Diastolic blood pressure \n",
"104478 Diastolic blood pressure \n",
"\n",
" INITIAL SAMPLE SIZE \\\n",
"0 2,079 European ancestry atopic dermatitis case... \n",
"1 2,079 European ancestry atopic dermatitis case... \n",
"2 2,079 European ancestry atopic dermatitis case... \n",
"3 2,079 European ancestry atopic dermatitis case... \n",
"4 2,079 European ancestry atopic dermatitis case... \n",
"5 2,079 European ancestry atopic dermatitis case... \n",
"6 2,079 European ancestry atopic dermatitis case... \n",
"7 2,079 European ancestry atopic dermatitis case... \n",
"8 2,079 European ancestry atopic dermatitis case... \n",
"9 2,079 European ancestry atopic dermatitis case... \n",
"10 2,079 European ancestry atopic dermatitis case... \n",
"11 2,079 European ancestry atopic dermatitis case... \n",
"12 2,079 European ancestry atopic dermatitis case... \n",
"13 2,079 European ancestry atopic dermatitis case... \n",
"14 2,079 European ancestry atopic dermatitis case... \n",
"15 2,079 European ancestry atopic dermatitis case... \n",
"16 2,079 European ancestry atopic dermatitis case... \n",
"17 2,079 European ancestry atopic dermatitis case... \n",
"18 2,079 European ancestry atopic dermatitis case... \n",
"19 2,079 European ancestry atopic dermatitis case... \n",
"20 2,079 European ancestry atopic dermatitis case... \n",
"21 2,079 European ancestry atopic dermatitis case... \n",
"22 2,079 European ancestry atopic dermatitis case... \n",
"23 2,079 European ancestry atopic dermatitis case... \n",
"24 2,079 European ancestry atopic dermatitis case... \n",
"25 2,079 European ancestry atopic dermatitis case... \n",
"26 2,079 European ancestry atopic dermatitis case... \n",
"27 2,079 European ancestry atopic dermatitis case... \n",
"28 2,079 European ancestry atopic dermatitis case... \n",
"29 2,079 European ancestry atopic dermatitis case... \n",
"... ... \n",
"104449 757,601 European ancestry individuals \n",
"104450 757,601 European ancestry individuals \n",
"104451 757,601 European ancestry individuals \n",
"104452 757,601 European ancestry individuals \n",
"104453 757,601 European ancestry individuals \n",
"104454 757,601 European ancestry individuals \n",
"104455 757,601 European ancestry individuals \n",
"104456 757,601 European ancestry individuals \n",
"104457 757,601 European ancestry individuals \n",
"104458 757,601 European ancestry individuals \n",
"104459 757,601 European ancestry individuals \n",
"104460 757,601 European ancestry individuals \n",
"104461 757,601 European ancestry individuals \n",
"104462 757,601 European ancestry individuals \n",
"104463 757,601 European ancestry individuals \n",
"104464 757,601 European ancestry individuals \n",
"104465 757,601 European ancestry individuals \n",
"104466 757,601 European ancestry individuals \n",
"104467 757,601 European ancestry individuals \n",
"104468 757,601 European ancestry individuals \n",
"104469 757,601 European ancestry individuals \n",
"104470 757,601 European ancestry individuals \n",
"104471 757,601 European ancestry individuals \n",
"104472 757,601 European ancestry individuals \n",
"104473 757,601 European ancestry individuals \n",
"104474 757,601 European ancestry individuals \n",
"104475 757,601 European ancestry individuals \n",
"104476 757,601 European ancestry individuals \n",
"104477 757,601 European ancestry individuals \n",
"104478 757,601 European ancestry individuals \n",
"\n",
" REPLICATION SAMPLE SIZE ... P-VALUE PVALUE_MLOG P-VALUE (TEXT) \\\n",
"0 NaN ... 4e-08 7.397940 (Opposed) \n",
"1 NaN ... 6e-08 7.221849 (Opposed) \n",
"2 NaN ... 2e-07 6.698970 (Opposed) \n",
"3 NaN ... 6e-07 6.221849 (Opposed) \n",
"4 NaN ... 6e-06 5.221849 (Opposed) \n",
"5 NaN ... 4e-12 11.397940 (Psoriasis) \n",
"6 NaN ... 2e-12 11.698970 (Psoriasis) \n",
"7 NaN ... 9e-16 15.045757 (Psoriasis) \n",
"8 NaN ... 1e-16 16.000000 (Psoriasis) \n",
"9 NaN ... 2e-14 13.698970 (Psoriasis) \n",
"10 NaN ... 3e-35 34.522879 (Psoriasis) \n",
"11 NaN ... 1e-25 25.000000 (Psoriasis) \n",
"12 NaN ... 2e-12 11.698970 (Psoriasis) \n",
"13 NaN ... 3e-12 11.522879 (Psoriasis) \n",
"14 NaN ... 1e-26 26.000000 (Psoriasis) \n",
"15 NaN ... 6e-18 17.221849 (Psoriasis) \n",
"16 NaN ... 4e-17 16.397940 (Psoriasis) \n",
"17 NaN ... 4e-16 15.397940 (Psoriasis) \n",
"18 NaN ... 3e-14 13.522879 (Psoriasis) \n",
"19 NaN ... 6e-13 12.221849 (Psoriasis) \n",
"20 NaN ... 2e-12 11.698970 (Psoriasis) \n",
"21 NaN ... 4e-12 11.397940 (Psoriasis) \n",
"22 NaN ... 6e-12 11.221849 (Psoriasis) \n",
"23 NaN ... 1e-11 11.000000 (Psoriasis) \n",
"24 NaN ... 4e-11 10.397940 (Psoriasis) \n",
"25 NaN ... 5e-11 10.301030 (Psoriasis) \n",
"26 NaN ... 5e-11 10.301030 (Psoriasis) \n",
"27 NaN ... 6e-11 10.221849 (Psoriasis) \n",
"28 NaN ... 1e-10 10.000000 (Psoriasis) \n",
"29 NaN ... 2e-10 9.698970 (Psoriasis) \n",
"... ... ... ... ... ... \n",
"104449 NaN ... 6e-10 9.221849 NaN \n",
"104450 NaN ... 7e-10 9.154902 NaN \n",
"104451 NaN ... 7e-10 9.154902 NaN \n",
"104452 NaN ... 8e-10 9.096910 NaN \n",
"104453 NaN ... 8e-10 9.096910 NaN \n",
"104454 NaN ... 9e-10 9.045757 NaN \n",
"104455 NaN ... 9e-10 9.045757 NaN \n",
"104456 NaN ... 1e-09 9.000000 NaN \n",
"104457 NaN ... 1e-09 9.000000 NaN \n",
"104458 NaN ... 1e-09 9.000000 NaN \n",
"104459 NaN ... 1e-09 9.000000 NaN \n",
"104460 NaN ... 1e-09 9.000000 NaN \n",
"104461 NaN ... 2e-09 8.698970 NaN \n",
"104462 NaN ... 2e-09 8.698970 NaN \n",
"104463 NaN ... 2e-09 8.698970 NaN \n",
"104464 NaN ... 3e-09 8.522879 NaN \n",
"104465 NaN ... 3e-09 8.522879 NaN \n",
"104466 NaN ... 3e-09 8.522879 NaN \n",
"104467 NaN ... 3e-09 8.522879 NaN \n",
"104468 NaN ... 4e-09 8.397940 NaN \n",
"104469 NaN ... 4e-09 8.397940 NaN \n",
"104470 NaN ... 4e-09 8.397940 NaN \n",
"104471 NaN ... 4e-09 8.397940 NaN \n",
"104472 NaN ... 4e-09 8.397940 NaN \n",
"104473 NaN ... 4e-09 8.397940 NaN \n",
"104474 NaN ... 4e-09 8.397940 NaN \n",
"104475 NaN ... 4e-09 8.397940 NaN \n",
"104476 NaN ... 4e-09 8.397940 NaN \n",
"104477 NaN ... 5e-09 8.301030 NaN \n",
"104478 NaN ... 5e-09 8.301030 NaN \n",
"\n",
" OR or BETA 95% CI (TEXT) \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"5 1.2000 [1.15–1.27] \n",
"6 1.2200 [1.15–1.30] \n",
"7 1.2700 [1.20–1.34] \n",
"8 1.2700 [1.20–1.35] \n",
"9 1.2900 [1.21–1.38] \n",
"10 1.3900 [1.32–1.47] \n",
"11 1.4500 [1.35–1.56] \n",
"12 1.4700 [1.32–1.64] \n",
"13 1.4700 [1.33–1.67] \n",
"14 1.5800 [1.45–1.72] \n",
"15 NaN NaN \n",
"16 NaN NaN \n",
"17 NaN NaN \n",
"18 NaN NaN \n",
"19 NaN NaN \n",
"20 NaN NaN \n",
"21 NaN NaN \n",
"22 NaN NaN \n",
"23 NaN NaN \n",
"24 NaN NaN \n",
"25 NaN NaN \n",
"26 NaN NaN \n",
"27 NaN NaN \n",
"28 NaN NaN \n",
"29 NaN NaN \n",
"... ... ... \n",
"104449 0.1203 [0.082-0.159] mmHg increase \n",
"104450 0.1150 [0.079-0.151] mmHg decrease \n",
"104451 0.1540 [0.1-0.2] mmHg decrease \n",
"104452 0.1071 [0.073-0.141] mmHg increase \n",
"104453 0.1173 [0.08-0.155] mmHg increase \n",
"104454 0.1242 [0.084-0.164] mmHg decrease \n",
"104455 0.1103 [0.075-0.146] mmHg decrease \n",
"104456 0.1096 [0.075-0.145] mmHg increase \n",
"104457 0.1233 [0.084-0.163] mmHg decrease \n",
"104458 0.1319 [0.09-0.174] mmHg increase \n",
"104459 0.1152 [0.078-0.152] mmHg increase \n",
"104460 0.1258 [0.085-0.166] mmHg increase \n",
"104461 0.1962 [0.13-0.26] mmHg decrease \n",
"104462 0.2140 [0.14-0.28] mmHg decrease \n",
"104463 0.1878 [0.13-0.25] mmHg increase \n",
"104464 0.1036 [0.069-0.138] mmHg decrease \n",
"104465 0.1511 [0.1-0.2] mmHg increase \n",
"104466 0.1391 [0.093-0.185] mmHg increase \n",
"104467 0.1400 [0.094-0.186] mmHg increase \n",
"104468 0.1244 [0.083-0.166] mmHg decrease \n",
"104469 0.1364 [0.091-0.182] mmHg increase \n",
"104470 0.1124 [0.075-0.15] mmHg increase \n",
"104471 0.1054 [0.07-0.14] mmHg increase \n",
"104472 0.1478 [0.099-0.197] mmHg decrease \n",
"104473 0.1760 [0.12-0.23] mmHg decrease \n",
"104474 0.1692 [0.11-0.23] mmHg increase \n",
"104475 0.1294 [0.086-0.173] mmHg increase \n",
"104476 0.1082 [0.072-0.144] mmHg decrease \n",
"104477 0.1072 [0.071-0.143] mmHg decrease \n",
"104478 0.1394 [0.093-0.186] mmHg decrease \n",
"\n",
" PLATFORM [SNPS PASSING QC] CNV my_index x \\\n",
"0 Affymetrix, Illumina [~ 5200000] N 0 0 \n",
"1 Affymetrix, Illumina [~ 5200000] N 1 1 \n",
"2 Affymetrix, Illumina [~ 5200000] N 2 2 \n",
"3 Affymetrix, Illumina [~ 5200000] N 3 3 \n",
"4 Affymetrix, Illumina [~ 5200000] N 4 4 \n",
"5 Affymetrix, Illumina [~ 5200000] N 5 5 \n",
"6 Affymetrix, Illumina [~ 5200000] N 6 6 \n",
"7 Affymetrix, Illumina [~ 5200000] N 7 7 \n",
"8 Affymetrix, Illumina [~ 5200000] N 8 8 \n",
"9 Affymetrix, Illumina [~ 5200000] N 9 9 \n",
"10 Affymetrix, Illumina [~ 5200000] N 10 10 \n",
"11 Affymetrix, Illumina [~ 5200000] N 11 11 \n",
"12 Affymetrix, Illumina [~ 5200000] N 12 12 \n",
"13 Affymetrix, Illumina [~ 5200000] N 13 13 \n",
"14 Affymetrix, Illumina [~ 5200000] N 14 14 \n",
"15 Affymetrix, Illumina [~ 5200000] N 15 15 \n",
"16 Affymetrix, Illumina [~ 5200000] N 16 16 \n",
"17 Affymetrix, Illumina [~ 5200000] N 17 17 \n",
"18 Affymetrix, Illumina [~ 5200000] N 18 18 \n",
"19 Affymetrix, Illumina [~ 5200000] N 19 19 \n",
"20 Affymetrix, Illumina [~ 5200000] N 20 20 \n",
"21 Affymetrix, Illumina [~ 5200000] N 21 21 \n",
"22 Affymetrix, Illumina [~ 5200000] N 22 22 \n",
"23 Affymetrix, Illumina [~ 5200000] N 23 23 \n",
"24 Affymetrix, Illumina [~ 5200000] N 24 24 \n",
"25 Affymetrix, Illumina [~ 5200000] N 25 25 \n",
"26 Affymetrix, Illumina [~ 5200000] N 26 26 \n",
"27 Affymetrix, Illumina [~ 5200000] N 27 27 \n",
"28 Affymetrix, Illumina [~ 5200000] N 28 28 \n",
"29 Affymetrix, Illumina [~ 5200000] N 29 29 \n",
"... ... ... ... ... \n",
"104449 Affymetrix, Illumina [~ 7100000] (imputed) N 104449 104449 \n",
"104450 Affymetrix, Illumina [~ 7100000] (imputed) N 104450 104450 \n",
"104451 Affymetrix, Illumina [~ 7100000] (imputed) N 104451 104451 \n",
"104452 Affymetrix, Illumina [~ 7100000] (imputed) N 104452 104452 \n",
"104453 Affymetrix, Illumina [~ 7100000] (imputed) N 104453 104453 \n",
"104454 Affymetrix, Illumina [~ 7100000] (imputed) N 104454 104454 \n",
"104455 Affymetrix, Illumina [~ 7100000] (imputed) N 104455 104455 \n",
"104456 Affymetrix, Illumina [~ 7100000] (imputed) N 104456 104456 \n",
"104457 Affymetrix, Illumina [~ 7100000] (imputed) N 104457 104457 \n",
"104458 Affymetrix, Illumina [~ 7100000] (imputed) N 104458 104458 \n",
"104459 Affymetrix, Illumina [~ 7100000] (imputed) N 104459 104459 \n",
"104460 Affymetrix, Illumina [~ 7100000] (imputed) N 104460 104460 \n",
"104461 Affymetrix, Illumina [~ 7100000] (imputed) N 104461 104461 \n",
"104462 Affymetrix, Illumina [~ 7100000] (imputed) N 104462 104462 \n",
"104463 Affymetrix, Illumina [~ 7100000] (imputed) N 104463 104463 \n",
"104464 Affymetrix, Illumina [~ 7100000] (imputed) N 104464 104464 \n",
"104465 Affymetrix, Illumina [~ 7100000] (imputed) N 104465 104465 \n",
"104466 Affymetrix, Illumina [~ 7100000] (imputed) N 104466 104466 \n",
"104467 Affymetrix, Illumina [~ 7100000] (imputed) N 104467 104467 \n",
"104468 Affymetrix, Illumina [~ 7100000] (imputed) N 104468 104468 \n",
"104469 Affymetrix, Illumina [~ 7100000] (imputed) N 104469 104469 \n",
"104470 Affymetrix, Illumina [~ 7100000] (imputed) N 104470 104470 \n",
"104471 Affymetrix, Illumina [~ 7100000] (imputed) N 104471 104471 \n",
"104472 Affymetrix, Illumina [~ 7100000] (imputed) N 104472 104472 \n",
"104473 Affymetrix, Illumina [~ 7100000] (imputed) N 104473 104473 \n",
"104474 Affymetrix, Illumina [~ 7100000] (imputed) N 104474 104474 \n",
"104475 Affymetrix, Illumina [~ 7100000] (imputed) N 104475 104475 \n",
"104476 Affymetrix, Illumina [~ 7100000] (imputed) N 104476 104476 \n",
"104477 Affymetrix, Illumina [~ 7100000] (imputed) N 104477 104477 \n",
"104478 Affymetrix, Illumina [~ 7100000] (imputed) N 104478 104478 \n",
"\n",
" y \n",
"0 2015-01-08 \n",
"1 2015-01-08 \n",
"2 2015-01-08 \n",
"3 2015-01-08 \n",
"4 2015-01-08 \n",
"5 2015-01-08 \n",
"6 2015-01-08 \n",
"7 2015-01-08 \n",
"8 2015-01-08 \n",
"9 2015-01-08 \n",
"10 2015-01-08 \n",
"11 2015-01-08 \n",
"12 2015-01-08 \n",
"13 2015-01-08 \n",
"14 2015-01-08 \n",
"15 2015-01-08 \n",
"16 2015-01-08 \n",
"17 2015-01-08 \n",
"18 2015-01-08 \n",
"19 2015-01-08 \n",
"20 2015-01-08 \n",
"21 2015-01-08 \n",
"22 2015-01-08 \n",
"23 2015-01-08 \n",
"24 2015-01-08 \n",
"25 2015-01-08 \n",
"26 2015-01-08 \n",
"27 2015-01-08 \n",
"28 2015-01-08 \n",
"29 2015-01-08 \n",
"... ... \n",
"104449 2018-09-17 \n",
"104450 2018-09-17 \n",
"104451 2018-09-17 \n",
"104452 2018-09-17 \n",
"104453 2018-09-17 \n",
"104454 2018-09-17 \n",
"104455 2018-09-17 \n",
"104456 2018-09-17 \n",
"104457 2018-09-17 \n",
"104458 2018-09-17 \n",
"104459 2018-09-17 \n",
"104460 2018-09-17 \n",
"104461 2018-09-17 \n",
"104462 2018-09-17 \n",
"104463 2018-09-17 \n",
"104464 2018-09-17 \n",
"104465 2018-09-17 \n",
"104466 2018-09-17 \n",
"104467 2018-09-17 \n",
"104468 2018-09-17 \n",
"104469 2018-09-17 \n",
"104470 2018-09-17 \n",
"104471 2018-09-17 \n",
"104472 2018-09-17 \n",
"104473 2018-09-17 \n",
"104474 2018-09-17 \n",
"104475 2018-09-17 \n",
"104476 2018-09-17 \n",
"104477 2018-09-17 \n",
"104478 2018-09-17 \n",
"\n",
"[101029 rows x 37 columns]"
]
},
"execution_count": 129,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[gwas['CHR_ID'].isin(list(map(str, range(1,23))) + ['X', 'Y'])]"
]
},
{
"cell_type": "code",
"execution_count": 132,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>A</th>\n",
" <th>B</th>\n",
" <th>C</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>aa</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>bb</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>cc</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>dd</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" A B C\n",
"0 1 aa True\n",
"1 2 bb False\n",
"2 3 cc False\n",
"3 4 dd True"
]
},
"execution_count": 132,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"data={\"A\": [1,2,3,4], \"B\": [\"aa\", \"bb\", \"cc\", \"dd\"], \"C\": [True, False, False, True]}\n",
"df = pd.DataFrame(data)\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 134,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{0: {'A': 1, 'B': 'aa', 'C': True},\n",
" 1: {'A': 2, 'B': 'bb', 'C': False},\n",
" 2: {'A': 3, 'B': 'cc', 'C': False},\n",
" 3: {'A': 4, 'B': 'dd', 'C': True}}"
]
},
"execution_count": 134,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.to_dict('index') "
]
},
{
"cell_type": "code",
"execution_count": 135,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'A': {0: 1, 1: 2, 2: 3, 3: 4},\n",
" 'B': {0: 'aa', 1: 'bb', 2: 'cc', 3: 'dd'},\n",
" 'C': {0: True, 1: False, 2: False, 3: True}}"
]
},
"execution_count": 135,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.to_dict()"
]
},
{
"cell_type": "code",
"execution_count": 137,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>A</th>\n",
" <th>B</th>\n",
" <th>C</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>aa</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>bb</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>aa</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>bb</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" A B C\n",
"0 1 aa True\n",
"1 2 bb False\n",
"2 3 aa False\n",
"3 4 bb True"
]
},
"execution_count": 137,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data={\"A\": [1,2,3,4], \"B\": [\"aa\", \"bb\", \"aa\", \"bb\"], \"C\": [True, False, False, True]}\n",
"df = pd.DataFrame(data)\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 146,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"B\n",
"aa 1\n",
"bb 2\n",
"Name: A, dtype: int64"
]
},
"execution_count": 146,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['A'].aggregate('min')"
]
},
{
"cell_type": "code",
"execution_count": 147,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"B\n",
"aa False\n",
"bb False\n",
"Name: C, dtype: bool"
]
},
"execution_count": 147,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['C'].aggregate('min')"
]
},
{
"cell_type": "code",
"execution_count": 151,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"B\n",
"aa 2\n",
"bb 3\n",
"Name: A, dtype: int64"
]
},
"execution_count": 151,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['A'].aggregate('mean')"
]
},
{
"cell_type": "code",
"execution_count": 153,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"B\n",
"aa 2\n",
"bb 2\n",
"Name: A, dtype: int64"
]
},
"execution_count": 153,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['A'].aggregate('count')"
]
},
{
"cell_type": "code",
"execution_count": 155,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"B\n",
"aa 4\n",
"bb 6\n",
"Name: A, dtype: int64"
]
},
"execution_count": 155,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['A'].aggregate('sum')"
]
},
{
"cell_type": "code",
"execution_count": 156,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"B\n",
"aa True\n",
"bb True\n",
"Name: C, dtype: bool"
]
},
"execution_count": 156,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['C'].aggregate('sum')"
]
},
{
"cell_type": "code",
"execution_count": 157,
"metadata": {},
"outputs": [],
"source": [
"def f(x):\n",
" return sum(x)/10"
]
},
{
"cell_type": "code",
"execution_count": 158,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"B\n",
"aa 0.4\n",
"bb 0.6\n",
"Name: A, dtype: float64"
]
},
"execution_count": 158,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['A'].aggregate(f)"
]
},
{
"cell_type": "code",
"execution_count": 165,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>sum</th>\n",
" <th>f</th>\n",
" </tr>\n",
" <tr>\n",
" <th>B</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>aa</th>\n",
" <td>4</td>\n",
" <td>0.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>bb</th>\n",
" <td>6</td>\n",
" <td>0.6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" sum f\n",
"B \n",
"aa 4 0.4\n",
"bb 6 0.6"
]
},
"execution_count": 165,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.groupby('B')['A'].aggregate(['sum', f])"
]
},
{
"cell_type": "code",
"execution_count": 166,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 167,
"metadata": {},
"outputs": [],
"source": [
"a = np.array(df.groupby('B')['A'].aggregate(['sum', f]))"
]
},
{
"cell_type": "code",
"execution_count": 168,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[4. , 0.4],\n",
" [6. , 0.6]])"
]
},
"execution_count": 168,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 161,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 161,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sum([True, False, True])"
]
},
{
"cell_type": "code",
"execution_count": 177,
"metadata": {},
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" DATE ADDED TO CATALOG PUBMEDID FIRST AUTHOR DATE \\\n",
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"\n",
" JOURNAL LINK \\\n",
"193 Nat Commun www.ncbi.nlm.nih.gov/pubmed/26151821 \n",
"383 World J Biol Psychiatry www.ncbi.nlm.nih.gov/pubmed/26249676 \n",
"\n",
" STUDY \\\n",
"193 Genome-wide association study of colorectal ca... \n",
"383 Genetic underpinnings of left superior tempora... \n",
"\n",
" DISEASE/TRAIT \\\n",
"193 Colorectal cancer \n",
"383 Left superior temporal gyrus thickness (schizo... \n",
"\n",
" INITIAL SAMPLE SIZE \\\n",
"193 18,299 European ancestry cases, 19,656 Europea... \n",
"383 113 schizophrenia cases, 126 controls \n",
"\n",
" REPLICATION SAMPLE SIZE ... P-VALUE \\\n",
"193 4,725 East Asian ancestry cases, 9,969 East As... ... 4e-08 \n",
"383 NaN ... 2e-06 \n",
"\n",
" PVALUE_MLOG P-VALUE (TEXT) OR or BETA 95% CI (TEXT) \\\n",
"193 7.39794 NaN 1.090 [1.06-1.12] \n",
"383 5.69897 NaN 0.275 [NR] unit decrease \n",
"\n",
" PLATFORM [SNPS PASSING QC] CNV my_index x y \n",
"193 Affymetrix, Illumina [~ 2500000] (imputed) N 193 193 2015-07-07 \n",
"383 Illumina [1067955] (imputed) N 383 383 2015-08-07 \n",
"\n",
"[2 rows x 37 columns]"
]
},
"execution_count": 177,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[gwas['FIRST AUTHOR'].str.contains('R') & gwas['REGION'].str.contains('10q')][:2]"
]
},
{
"cell_type": "code",
"execution_count": 181,
"metadata": {},
"outputs": [
{
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" <td>7.39794</td>\n",
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" <td>N</td>\n",
" <td>383</td>\n",
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" <td>2015-08-07</td>\n",
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" DATE ADDED TO CATALOG PUBMEDID FIRST AUTHOR DATE \\\n",
"193 2016-06-10 26151821 Schumacher FR 2015-07-07 \n",
"383 2016-09-12 26249676 Wolthusen RP 2015-08-07 \n",
"\n",
" JOURNAL LINK \\\n",
"193 Nat Commun www.ncbi.nlm.nih.gov/pubmed/26151821 \n",
"383 World J Biol Psychiatry www.ncbi.nlm.nih.gov/pubmed/26249676 \n",
"\n",
" STUDY \\\n",
"193 Genome-wide association study of colorectal ca... \n",
"383 Genetic underpinnings of left superior tempora... \n",
"\n",
" DISEASE/TRAIT \\\n",
"193 Colorectal cancer \n",
"383 Left superior temporal gyrus thickness (schizo... \n",
"\n",
" INITIAL SAMPLE SIZE \\\n",
"193 18,299 European ancestry cases, 19,656 Europea... \n",
"383 113 schizophrenia cases, 126 controls \n",
"\n",
" REPLICATION SAMPLE SIZE ... P-VALUE \\\n",
"193 4,725 East Asian ancestry cases, 9,969 East As... ... 4e-08 \n",
"383 NaN ... 2e-06 \n",
"\n",
" PVALUE_MLOG P-VALUE (TEXT) OR or BETA 95% CI (TEXT) \\\n",
"193 7.39794 NaN 1.090 [1.06-1.12] \n",
"383 5.69897 NaN 0.275 [NR] unit decrease \n",
"\n",
" PLATFORM [SNPS PASSING QC] CNV my_index x y \n",
"193 Affymetrix, Illumina [~ 2500000] (imputed) N 193 193 2015-07-07 \n",
"383 Illumina [1067955] (imputed) N 383 383 2015-08-07 \n",
"\n",
"[2 rows x 37 columns]"
]
},
"execution_count": 181,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[reduce(my_and, [gwas['FIRST AUTHOR'].str.contains('R'), gwas['REGION'].str.contains('10q')])][:2]"
]
},
{
"cell_type": "code",
"execution_count": 169,
"metadata": {},
"outputs": [],
"source": [
"from functools import reduce"
]
},
{
"cell_type": "code",
"execution_count": 191,
"metadata": {},
"outputs": [],
"source": [
"def f(x,y):\n",
" return x*y\n",
"def g(x):\n",
" return x**3"
]
},
{
"cell_type": "code",
"execution_count": 192,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"18"
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"execution_count": 192,
"metadata": {},
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"source": [
"reduce(f, [1,2,3,3])"
]
},
{
"cell_type": "code",
"execution_count": 193,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[1, 8, 27, 27]"
]
},
"execution_count": 193,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(map(g, [1,2,3,3]))"
]
},
{
"cell_type": "code",
"execution_count": 194,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"5832"
]
},
"execution_count": 194,
"metadata": {},
"output_type": "execute_result"
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"source": [
"reduce(f, map(g, [1,2,3,3]))"
]
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"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
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{
"cell_type": "code",
"execution_count": 172,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 172,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"True & True"
]
},
{
"cell_type": "code",
"execution_count": 173,
"metadata": {},
"outputs": [],
"source": [
"def my_and(x,y):\n",
" return x&y"
]
},
{
"cell_type": "code",
"execution_count": 189,
"metadata": {},
"outputs": [],
"source": [
"def f1(letter):\n",
" return gwas['FIRST AUTHOR'].str.contains(letter, case=False)"
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{
"cell_type": "code",
"execution_count": 190,
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" <td>4</td>\n",
" <td>2015-01-08</td>\n",
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" <tr>\n",
" <th>5</th>\n",
" <td>2015-12-18</td>\n",
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" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.22</td>\n",
" <td>[1.15–1.30]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>6</td>\n",
" <td>6</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>9e-16</td>\n",
" <td>15.045757</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.27</td>\n",
" <td>[1.20–1.34]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>7</td>\n",
" <td>7</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-16</td>\n",
" <td>16.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.27</td>\n",
" <td>[1.20–1.35]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>8</td>\n",
" <td>8</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-14</td>\n",
" <td>13.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.29</td>\n",
" <td>[1.21–1.38]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>9</td>\n",
" <td>9</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-35</td>\n",
" <td>34.522879</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.39</td>\n",
" <td>[1.32–1.47]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>10</td>\n",
" <td>10</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-25</td>\n",
" <td>25.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.45</td>\n",
" <td>[1.35–1.56]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>11</td>\n",
" <td>11</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.47</td>\n",
" <td>[1.32–1.64]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>12</td>\n",
" <td>12</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-12</td>\n",
" <td>11.522879</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.47</td>\n",
" <td>[1.33–1.67]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>13</td>\n",
" <td>13</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-26</td>\n",
" <td>26.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>1.58</td>\n",
" <td>[1.45–1.72]</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>14</td>\n",
" <td>14</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-18</td>\n",
" <td>17.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>15</td>\n",
" <td>15</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-17</td>\n",
" <td>16.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>16</td>\n",
" <td>16</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-16</td>\n",
" <td>15.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>17</td>\n",
" <td>17</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-14</td>\n",
" <td>13.522879</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>18</td>\n",
" <td>18</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-13</td>\n",
" <td>12.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>19</td>\n",
" <td>19</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>20</td>\n",
" <td>20</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-12</td>\n",
" <td>11.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>21</td>\n",
" <td>21</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-12</td>\n",
" <td>11.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>22</td>\n",
" <td>22</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-11</td>\n",
" <td>11.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>23</td>\n",
" <td>23</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-11</td>\n",
" <td>10.397940</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>24</td>\n",
" <td>24</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-11</td>\n",
" <td>10.301030</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>25</td>\n",
" <td>25</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-11</td>\n",
" <td>10.301030</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>26</td>\n",
" <td>26</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-11</td>\n",
" <td>10.221849</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>27</td>\n",
" <td>27</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-10</td>\n",
" <td>10.000000</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>28</td>\n",
" <td>28</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>2015-12-18</td>\n",
" <td>25574825</td>\n",
" <td>Baurecht H</td>\n",
" <td>2015-01-08</td>\n",
" <td>Am J Hum Genet</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/25574825</td>\n",
" <td>Genome-wide comparative analysis of atopic der...</td>\n",
" <td>Inflammatory skin disease</td>\n",
" <td>2,079 European ancestry atopic dermatitis case...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-10</td>\n",
" <td>9.698970</td>\n",
" <td>(Psoriasis)</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Affymetrix, Illumina [~ 5200000]</td>\n",
" <td>N</td>\n",
" <td>29</td>\n",
" <td>29</td>\n",
" <td>2015-01-08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103390</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Midgestational cytokine/chemokine levels (mate...</td>\n",
" <td>790 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-09</td>\n",
" <td>8.698970</td>\n",
" <td>(CCL11)</td>\n",
" <td>1.50</td>\n",
" <td>[1.03-1.97] unit decrease</td>\n",
" <td>Affymetrix [629686]</td>\n",
" <td>N</td>\n",
" <td>103390</td>\n",
" <td>103390</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103391</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Midgestational cytokine/chemokine levels (mate...</td>\n",
" <td>790 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>(sIL2R-alpha)</td>\n",
" <td>0.65</td>\n",
" <td>[0.43-0.87] unit increase</td>\n",
" <td>Affymetrix [629686]</td>\n",
" <td>N</td>\n",
" <td>103391</td>\n",
" <td>103391</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103392</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Midgestational cytokine/chemokine levels (mate...</td>\n",
" <td>790 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-08</td>\n",
" <td>7.698970</td>\n",
" <td>(IL1-alpha)</td>\n",
" <td>0.74</td>\n",
" <td>[0.49-0.99] unit decrease</td>\n",
" <td>Affymetrix [629686]</td>\n",
" <td>N</td>\n",
" <td>103392</td>\n",
" <td>103392</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103393</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (maternal g...</td>\n",
" <td>790 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-08</td>\n",
" <td>7.522879</td>\n",
" <td>(CXCL5)</td>\n",
" <td>2.17</td>\n",
" <td>[1.43-2.91] unit decrease</td>\n",
" <td>Affymetrix [629686]</td>\n",
" <td>N</td>\n",
" <td>103393</td>\n",
" <td>103393</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103394</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (maternal g...</td>\n",
" <td>790 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-08</td>\n",
" <td>8.000000</td>\n",
" <td>(CCL24)</td>\n",
" <td>1.52</td>\n",
" <td>[1.03-2.01] unit decrease</td>\n",
" <td>Affymetrix [629686]</td>\n",
" <td>N</td>\n",
" <td>103394</td>\n",
" <td>103394</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103395</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (maternal g...</td>\n",
" <td>790 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-09</td>\n",
" <td>9.000000</td>\n",
" <td>(IL-16)</td>\n",
" <td>0.36</td>\n",
" <td>[0.24-0.48] unit decrease</td>\n",
" <td>Affymetrix [629686]</td>\n",
" <td>N</td>\n",
" <td>103395</td>\n",
" <td>103395</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103396</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Midgestational cytokine/chemokine levels (feta...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>1e-08</td>\n",
" <td>8.000000</td>\n",
" <td>(sIL2R-alpha)</td>\n",
" <td>0.42</td>\n",
" <td>[0.28-0.56] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103396</td>\n",
" <td>103396</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103946</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>9e-21</td>\n",
" <td>20.045757</td>\n",
" <td>(CCL17)</td>\n",
" <td>0.53</td>\n",
" <td>[0.43-0.63] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103946</td>\n",
" <td>103946</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103947</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-20</td>\n",
" <td>19.522879</td>\n",
" <td>(CCL19)</td>\n",
" <td>0.48</td>\n",
" <td>[0.38-0.58] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103947</td>\n",
" <td>103947</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103948</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-19</td>\n",
" <td>18.522879</td>\n",
" <td>(CXCL9)</td>\n",
" <td>0.36</td>\n",
" <td>[0.28-0.44] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103948</td>\n",
" <td>103948</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103949</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>8e-13</td>\n",
" <td>12.096910</td>\n",
" <td>(CCL7)</td>\n",
" <td>0.23</td>\n",
" <td>[0.17-0.29] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103949</td>\n",
" <td>103949</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103950</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-12</td>\n",
" <td>11.301030</td>\n",
" <td>(IFN-gamma)</td>\n",
" <td>0.24</td>\n",
" <td>[0.18-0.3] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103950</td>\n",
" <td>103950</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103951</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-12</td>\n",
" <td>11.698970</td>\n",
" <td>(IL-2)</td>\n",
" <td>0.27</td>\n",
" <td>[0.19-0.35] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103951</td>\n",
" <td>103951</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103952</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-11</td>\n",
" <td>10.698970</td>\n",
" <td>(IL-6)</td>\n",
" <td>0.26</td>\n",
" <td>[0.18-0.34] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103952</td>\n",
" <td>103952</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103953</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-11</td>\n",
" <td>10.698970</td>\n",
" <td>(IL-10)</td>\n",
" <td>0.20</td>\n",
" <td>[0.14-0.26] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103953</td>\n",
" <td>103953</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103954</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-10</td>\n",
" <td>9.397940</td>\n",
" <td>(IL-1beta)</td>\n",
" <td>0.22</td>\n",
" <td>[0.16-0.28] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103954</td>\n",
" <td>103954</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103955</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>9e-10</td>\n",
" <td>9.045757</td>\n",
" <td>(CXCL13)</td>\n",
" <td>0.17</td>\n",
" <td>[0.11-0.23] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103955</td>\n",
" <td>103955</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103956</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-08</td>\n",
" <td>7.698970</td>\n",
" <td>(CX3CL1)</td>\n",
" <td>0.16</td>\n",
" <td>[0.1-0.22] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103956</td>\n",
" <td>103956</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103957</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-100</td>\n",
" <td>99.522879</td>\n",
" <td>(CCL23)</td>\n",
" <td>0.63</td>\n",
" <td>[0.59-0.67] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103957</td>\n",
" <td>103957</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103958</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-25</td>\n",
" <td>24.301030</td>\n",
" <td>(CCL15)</td>\n",
" <td>0.47</td>\n",
" <td>[0.39-0.55] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103958</td>\n",
" <td>103958</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103959</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-14</td>\n",
" <td>13.698970</td>\n",
" <td>(CXCL11)</td>\n",
" <td>0.24</td>\n",
" <td>[0.18-0.3] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103959</td>\n",
" <td>103959</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103960</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>6e-09</td>\n",
" <td>8.221849</td>\n",
" <td>(CXCL6)</td>\n",
" <td>0.10</td>\n",
" <td>[0.061-0.139] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103960</td>\n",
" <td>103960</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103961</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>5e-08</td>\n",
" <td>7.301030</td>\n",
" <td>(CCL24)</td>\n",
" <td>0.86</td>\n",
" <td>[0.55-1.17] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103961</td>\n",
" <td>103961</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103962</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-10</td>\n",
" <td>9.522879</td>\n",
" <td>(CCL21)</td>\n",
" <td>0.20</td>\n",
" <td>[0.14-0.26] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103962</td>\n",
" <td>103962</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103963</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>3e-08</td>\n",
" <td>7.522879</td>\n",
" <td>(CXCL9)</td>\n",
" <td>0.29</td>\n",
" <td>[0.19-0.39] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103963</td>\n",
" <td>103963</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103964</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>4e-09</td>\n",
" <td>8.397940</td>\n",
" <td>(CCL19)</td>\n",
" <td>0.42</td>\n",
" <td>[0.28-0.56] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103964</td>\n",
" <td>103964</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103965</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-10</td>\n",
" <td>9.698970</td>\n",
" <td>(CCL17)</td>\n",
" <td>0.48</td>\n",
" <td>[0.34-0.62] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103965</td>\n",
" <td>103965</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103966</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-09</td>\n",
" <td>8.698970</td>\n",
" <td>(IL-4)</td>\n",
" <td>0.40</td>\n",
" <td>[0.26-0.54] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103966</td>\n",
" <td>103966</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103967</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>2e-08</td>\n",
" <td>7.698970</td>\n",
" <td>(CXCL12)</td>\n",
" <td>0.09</td>\n",
" <td>[0.051-0.129] unit decrease</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103967</td>\n",
" <td>103967</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103968</th>\n",
" <td>2018-11-29</td>\n",
" <td>30134952</td>\n",
" <td>Traglia M</td>\n",
" <td>2018-08-22</td>\n",
" <td>Genome Med</td>\n",
" <td>www.ncbi.nlm.nih.gov/pubmed/30134952</td>\n",
" <td>Cross-genetic determination of maternal and ne...</td>\n",
" <td>Neonatal cytokine/chemokine levels (fetal gene...</td>\n",
" <td>764 Hispanic, European, Asian, South Asian or ...</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>9e-07</td>\n",
" <td>6.045757</td>\n",
" <td>(IL-8)</td>\n",
" <td>0.42</td>\n",
" <td>[0.24-0.6] unit increase</td>\n",
" <td>Affymetrix [622716]</td>\n",
" <td>N</td>\n",
" <td>103968</td>\n",
" <td>103968</td>\n",
" <td>2018-08-22</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>4676 rows × 37 columns</p>\n",
"</div>"
],
"text/plain": [
" DATE ADDED TO CATALOG PUBMEDID FIRST AUTHOR DATE \\\n",
"0 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"1 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"2 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"3 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"4 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"5 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"6 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"7 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"8 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"9 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"10 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"11 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"12 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"13 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"14 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"15 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"16 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"17 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"18 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"19 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"20 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"21 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"22 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"23 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"24 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"25 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"26 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"27 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"28 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"29 2015-12-18 25574825 Baurecht H 2015-01-08 \n",
"... ... ... ... ... \n",
"103390 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103391 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103392 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103393 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103394 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103395 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103396 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103946 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103947 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103948 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103949 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103950 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103951 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103952 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103953 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103954 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103955 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103956 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103957 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103958 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103959 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103960 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103961 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103962 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103963 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103964 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103965 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103966 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103967 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"103968 2018-11-29 30134952 Traglia M 2018-08-22 \n",
"\n",
" JOURNAL LINK \\\n",
"0 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"1 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"2 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"3 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"4 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"5 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"6 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"7 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"8 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"9 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"10 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"11 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"12 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"13 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"14 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"15 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"16 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"17 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"18 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"19 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"20 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"21 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"22 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"23 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"24 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"25 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"26 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"27 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"28 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"29 Am J Hum Genet www.ncbi.nlm.nih.gov/pubmed/25574825 \n",
"... ... ... \n",
"103390 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103391 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103392 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103393 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103394 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103395 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103396 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103946 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103947 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103948 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103949 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103950 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103951 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103952 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103953 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103954 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103955 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103956 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103957 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103958 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103959 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103960 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103961 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103962 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103963 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103964 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103965 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103966 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103967 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"103968 Genome Med www.ncbi.nlm.nih.gov/pubmed/30134952 \n",
"\n",
" STUDY \\\n",
"0 Genome-wide comparative analysis of atopic der... \n",
"1 Genome-wide comparative analysis of atopic der... \n",
"2 Genome-wide comparative analysis of atopic der... \n",
"3 Genome-wide comparative analysis of atopic der... \n",
"4 Genome-wide comparative analysis of atopic der... \n",
"5 Genome-wide comparative analysis of atopic der... \n",
"6 Genome-wide comparative analysis of atopic der... \n",
"7 Genome-wide comparative analysis of atopic der... \n",
"8 Genome-wide comparative analysis of atopic der... \n",
"9 Genome-wide comparative analysis of atopic der... \n",
"10 Genome-wide comparative analysis of atopic der... \n",
"11 Genome-wide comparative analysis of atopic der... \n",
"12 Genome-wide comparative analysis of atopic der... \n",
"13 Genome-wide comparative analysis of atopic der... \n",
"14 Genome-wide comparative analysis of atopic der... \n",
"15 Genome-wide comparative analysis of atopic der... \n",
"16 Genome-wide comparative analysis of atopic der... \n",
"17 Genome-wide comparative analysis of atopic der... \n",
"18 Genome-wide comparative analysis of atopic der... \n",
"19 Genome-wide comparative analysis of atopic der... \n",
"20 Genome-wide comparative analysis of atopic der... \n",
"21 Genome-wide comparative analysis of atopic der... \n",
"22 Genome-wide comparative analysis of atopic der... \n",
"23 Genome-wide comparative analysis of atopic der... \n",
"24 Genome-wide comparative analysis of atopic der... \n",
"25 Genome-wide comparative analysis of atopic der... \n",
"26 Genome-wide comparative analysis of atopic der... \n",
"27 Genome-wide comparative analysis of atopic der... \n",
"28 Genome-wide comparative analysis of atopic der... \n",
"29 Genome-wide comparative analysis of atopic der... \n",
"... ... \n",
"103390 Cross-genetic determination of maternal and ne... \n",
"103391 Cross-genetic determination of maternal and ne... \n",
"103392 Cross-genetic determination of maternal and ne... \n",
"103393 Cross-genetic determination of maternal and ne... \n",
"103394 Cross-genetic determination of maternal and ne... \n",
"103395 Cross-genetic determination of maternal and ne... \n",
"103396 Cross-genetic determination of maternal and ne... \n",
"103946 Cross-genetic determination of maternal and ne... \n",
"103947 Cross-genetic determination of maternal and ne... \n",
"103948 Cross-genetic determination of maternal and ne... \n",
"103949 Cross-genetic determination of maternal and ne... \n",
"103950 Cross-genetic determination of maternal and ne... \n",
"103951 Cross-genetic determination of maternal and ne... \n",
"103952 Cross-genetic determination of maternal and ne... \n",
"103953 Cross-genetic determination of maternal and ne... \n",
"103954 Cross-genetic determination of maternal and ne... \n",
"103955 Cross-genetic determination of maternal and ne... \n",
"103956 Cross-genetic determination of maternal and ne... \n",
"103957 Cross-genetic determination of maternal and ne... \n",
"103958 Cross-genetic determination of maternal and ne... \n",
"103959 Cross-genetic determination of maternal and ne... \n",
"103960 Cross-genetic determination of maternal and ne... \n",
"103961 Cross-genetic determination of maternal and ne... \n",
"103962 Cross-genetic determination of maternal and ne... \n",
"103963 Cross-genetic determination of maternal and ne... \n",
"103964 Cross-genetic determination of maternal and ne... \n",
"103965 Cross-genetic determination of maternal and ne... \n",
"103966 Cross-genetic determination of maternal and ne... \n",
"103967 Cross-genetic determination of maternal and ne... \n",
"103968 Cross-genetic determination of maternal and ne... \n",
"\n",
" DISEASE/TRAIT \\\n",
"0 Inflammatory skin disease \n",
"1 Inflammatory skin disease \n",
"2 Inflammatory skin disease \n",
"3 Inflammatory skin disease \n",
"4 Inflammatory skin disease \n",
"5 Inflammatory skin disease \n",
"6 Inflammatory skin disease \n",
"7 Inflammatory skin disease \n",
"8 Inflammatory skin disease \n",
"9 Inflammatory skin disease \n",
"10 Inflammatory skin disease \n",
"11 Inflammatory skin disease \n",
"12 Inflammatory skin disease \n",
"13 Inflammatory skin disease \n",
"14 Inflammatory skin disease \n",
"15 Inflammatory skin disease \n",
"16 Inflammatory skin disease \n",
"17 Inflammatory skin disease \n",
"18 Inflammatory skin disease \n",
"19 Inflammatory skin disease \n",
"20 Inflammatory skin disease \n",
"21 Inflammatory skin disease \n",
"22 Inflammatory skin disease \n",
"23 Inflammatory skin disease \n",
"24 Inflammatory skin disease \n",
"25 Inflammatory skin disease \n",
"26 Inflammatory skin disease \n",
"27 Inflammatory skin disease \n",
"28 Inflammatory skin disease \n",
"29 Inflammatory skin disease \n",
"... ... \n",
"103390 Midgestational cytokine/chemokine levels (mate... \n",
"103391 Midgestational cytokine/chemokine levels (mate... \n",
"103392 Midgestational cytokine/chemokine levels (mate... \n",
"103393 Neonatal cytokine/chemokine levels (maternal g... \n",
"103394 Neonatal cytokine/chemokine levels (maternal g... \n",
"103395 Neonatal cytokine/chemokine levels (maternal g... \n",
"103396 Midgestational cytokine/chemokine levels (feta... \n",
"103946 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103947 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103948 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103949 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103950 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103951 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103952 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103953 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103954 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103955 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103956 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103957 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103958 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103959 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103960 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103961 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103962 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103963 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103964 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103965 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103966 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103967 Neonatal cytokine/chemokine levels (fetal gene... \n",
"103968 Neonatal cytokine/chemokine levels (fetal gene... \n",
"\n",
" INITIAL SAMPLE SIZE \\\n",
"0 2,079 European ancestry atopic dermatitis case... \n",
"1 2,079 European ancestry atopic dermatitis case... \n",
"2 2,079 European ancestry atopic dermatitis case... \n",
"3 2,079 European ancestry atopic dermatitis case... \n",
"4 2,079 European ancestry atopic dermatitis case... \n",
"5 2,079 European ancestry atopic dermatitis case... \n",
"6 2,079 European ancestry atopic dermatitis case... \n",
"7 2,079 European ancestry atopic dermatitis case... \n",
"8 2,079 European ancestry atopic dermatitis case... \n",
"9 2,079 European ancestry atopic dermatitis case... \n",
"10 2,079 European ancestry atopic dermatitis case... \n",
"11 2,079 European ancestry atopic dermatitis case... \n",
"12 2,079 European ancestry atopic dermatitis case... \n",
"13 2,079 European ancestry atopic dermatitis case... \n",
"14 2,079 European ancestry atopic dermatitis case... \n",
"15 2,079 European ancestry atopic dermatitis case... \n",
"16 2,079 European ancestry atopic dermatitis case... \n",
"17 2,079 European ancestry atopic dermatitis case... \n",
"18 2,079 European ancestry atopic dermatitis case... \n",
"19 2,079 European ancestry atopic dermatitis case... \n",
"20 2,079 European ancestry atopic dermatitis case... \n",
"21 2,079 European ancestry atopic dermatitis case... \n",
"22 2,079 European ancestry atopic dermatitis case... \n",
"23 2,079 European ancestry atopic dermatitis case... \n",
"24 2,079 European ancestry atopic dermatitis case... \n",
"25 2,079 European ancestry atopic dermatitis case... \n",
"26 2,079 European ancestry atopic dermatitis case... \n",
"27 2,079 European ancestry atopic dermatitis case... \n",
"28 2,079 European ancestry atopic dermatitis case... \n",
"29 2,079 European ancestry atopic dermatitis case... \n",
"... ... \n",
"103390 790 Hispanic, European, Asian, South Asian or ... \n",
"103391 790 Hispanic, European, Asian, South Asian or ... \n",
"103392 790 Hispanic, European, Asian, South Asian or ... \n",
"103393 790 Hispanic, European, Asian, South Asian or ... \n",
"103394 790 Hispanic, European, Asian, South Asian or ... \n",
"103395 790 Hispanic, European, Asian, South Asian or ... \n",
"103396 764 Hispanic, European, Asian, South Asian or ... \n",
"103946 764 Hispanic, European, Asian, South Asian or ... \n",
"103947 764 Hispanic, European, Asian, South Asian or ... \n",
"103948 764 Hispanic, European, Asian, South Asian or ... \n",
"103949 764 Hispanic, European, Asian, South Asian or ... \n",
"103950 764 Hispanic, European, Asian, South Asian or ... \n",
"103951 764 Hispanic, European, Asian, South Asian or ... \n",
"103952 764 Hispanic, European, Asian, South Asian or ... \n",
"103953 764 Hispanic, European, Asian, South Asian or ... \n",
"103954 764 Hispanic, European, Asian, South Asian or ... \n",
"103955 764 Hispanic, European, Asian, South Asian or ... \n",
"103956 764 Hispanic, European, Asian, South Asian or ... \n",
"103957 764 Hispanic, European, Asian, South Asian or ... \n",
"103958 764 Hispanic, European, Asian, South Asian or ... \n",
"103959 764 Hispanic, European, Asian, South Asian or ... \n",
"103960 764 Hispanic, European, Asian, South Asian or ... \n",
"103961 764 Hispanic, European, Asian, South Asian or ... \n",
"103962 764 Hispanic, European, Asian, South Asian or ... \n",
"103963 764 Hispanic, European, Asian, South Asian or ... \n",
"103964 764 Hispanic, European, Asian, South Asian or ... \n",
"103965 764 Hispanic, European, Asian, South Asian or ... \n",
"103966 764 Hispanic, European, Asian, South Asian or ... \n",
"103967 764 Hispanic, European, Asian, South Asian or ... \n",
"103968 764 Hispanic, European, Asian, South Asian or ... \n",
"\n",
" REPLICATION SAMPLE SIZE ... P-VALUE PVALUE_MLOG P-VALUE (TEXT) \\\n",
"0 NaN ... 4e-08 7.397940 (Opposed) \n",
"1 NaN ... 6e-08 7.221849 (Opposed) \n",
"2 NaN ... 2e-07 6.698970 (Opposed) \n",
"3 NaN ... 6e-07 6.221849 (Opposed) \n",
"4 NaN ... 6e-06 5.221849 (Opposed) \n",
"5 NaN ... 4e-12 11.397940 (Psoriasis) \n",
"6 NaN ... 2e-12 11.698970 (Psoriasis) \n",
"7 NaN ... 9e-16 15.045757 (Psoriasis) \n",
"8 NaN ... 1e-16 16.000000 (Psoriasis) \n",
"9 NaN ... 2e-14 13.698970 (Psoriasis) \n",
"10 NaN ... 3e-35 34.522879 (Psoriasis) \n",
"11 NaN ... 1e-25 25.000000 (Psoriasis) \n",
"12 NaN ... 2e-12 11.698970 (Psoriasis) \n",
"13 NaN ... 3e-12 11.522879 (Psoriasis) \n",
"14 NaN ... 1e-26 26.000000 (Psoriasis) \n",
"15 NaN ... 6e-18 17.221849 (Psoriasis) \n",
"16 NaN ... 4e-17 16.397940 (Psoriasis) \n",
"17 NaN ... 4e-16 15.397940 (Psoriasis) \n",
"18 NaN ... 3e-14 13.522879 (Psoriasis) \n",
"19 NaN ... 6e-13 12.221849 (Psoriasis) \n",
"20 NaN ... 2e-12 11.698970 (Psoriasis) \n",
"21 NaN ... 4e-12 11.397940 (Psoriasis) \n",
"22 NaN ... 6e-12 11.221849 (Psoriasis) \n",
"23 NaN ... 1e-11 11.000000 (Psoriasis) \n",
"24 NaN ... 4e-11 10.397940 (Psoriasis) \n",
"25 NaN ... 5e-11 10.301030 (Psoriasis) \n",
"26 NaN ... 5e-11 10.301030 (Psoriasis) \n",
"27 NaN ... 6e-11 10.221849 (Psoriasis) \n",
"28 NaN ... 1e-10 10.000000 (Psoriasis) \n",
"29 NaN ... 2e-10 9.698970 (Psoriasis) \n",
"... ... ... ... ... ... \n",
"103390 NaN ... 2e-09 8.698970 (CCL11) \n",
"103391 NaN ... 4e-09 8.397940 (sIL2R-alpha) \n",
"103392 NaN ... 2e-08 7.698970 (IL1-alpha) \n",
"103393 NaN ... 3e-08 7.522879 (CXCL5) \n",
"103394 NaN ... 1e-08 8.000000 (CCL24) \n",
"103395 NaN ... 1e-09 9.000000 (IL-16) \n",
"103396 NaN ... 1e-08 8.000000 (sIL2R-alpha) \n",
"103946 NaN ... 9e-21 20.045757 (CCL17) \n",
"103947 NaN ... 3e-20 19.522879 (CCL19) \n",
"103948 NaN ... 3e-19 18.522879 (CXCL9) \n",
"103949 NaN ... 8e-13 12.096910 (CCL7) \n",
"103950 NaN ... 5e-12 11.301030 (IFN-gamma) \n",
"103951 NaN ... 2e-12 11.698970 (IL-2) \n",
"103952 NaN ... 2e-11 10.698970 (IL-6) \n",
"103953 NaN ... 2e-11 10.698970 (IL-10) \n",
"103954 NaN ... 4e-10 9.397940 (IL-1beta) \n",
"103955 NaN ... 9e-10 9.045757 (CXCL13) \n",
"103956 NaN ... 2e-08 7.698970 (CX3CL1) \n",
"103957 NaN ... 3e-100 99.522879 (CCL23) \n",
"103958 NaN ... 5e-25 24.301030 (CCL15) \n",
"103959 NaN ... 2e-14 13.698970 (CXCL11) \n",
"103960 NaN ... 6e-09 8.221849 (CXCL6) \n",
"103961 NaN ... 5e-08 7.301030 (CCL24) \n",
"103962 NaN ... 3e-10 9.522879 (CCL21) \n",
"103963 NaN ... 3e-08 7.522879 (CXCL9) \n",
"103964 NaN ... 4e-09 8.397940 (CCL19) \n",
"103965 NaN ... 2e-10 9.698970 (CCL17) \n",
"103966 NaN ... 2e-09 8.698970 (IL-4) \n",
"103967 NaN ... 2e-08 7.698970 (CXCL12) \n",
"103968 NaN ... 9e-07 6.045757 (IL-8) \n",
"\n",
" OR or BETA 95% CI (TEXT) \\\n",
"0 NaN NaN \n",
"1 NaN NaN \n",
"2 NaN NaN \n",
"3 NaN NaN \n",
"4 NaN NaN \n",
"5 1.20 [1.15–1.27] \n",
"6 1.22 [1.15–1.30] \n",
"7 1.27 [1.20–1.34] \n",
"8 1.27 [1.20–1.35] \n",
"9 1.29 [1.21–1.38] \n",
"10 1.39 [1.32–1.47] \n",
"11 1.45 [1.35–1.56] \n",
"12 1.47 [1.32–1.64] \n",
"13 1.47 [1.33–1.67] \n",
"14 1.58 [1.45–1.72] \n",
"15 NaN NaN \n",
"16 NaN NaN \n",
"17 NaN NaN \n",
"18 NaN NaN \n",
"19 NaN NaN \n",
"20 NaN NaN \n",
"21 NaN NaN \n",
"22 NaN NaN \n",
"23 NaN NaN \n",
"24 NaN NaN \n",
"25 NaN NaN \n",
"26 NaN NaN \n",
"27 NaN NaN \n",
"28 NaN NaN \n",
"29 NaN NaN \n",
"... ... ... \n",
"103390 1.50 [1.03-1.97] unit decrease \n",
"103391 0.65 [0.43-0.87] unit increase \n",
"103392 0.74 [0.49-0.99] unit decrease \n",
"103393 2.17 [1.43-2.91] unit decrease \n",
"103394 1.52 [1.03-2.01] unit decrease \n",
"103395 0.36 [0.24-0.48] unit decrease \n",
"103396 0.42 [0.28-0.56] unit decrease \n",
"103946 0.53 [0.43-0.63] unit decrease \n",
"103947 0.48 [0.38-0.58] unit decrease \n",
"103948 0.36 [0.28-0.44] unit decrease \n",
"103949 0.23 [0.17-0.29] unit decrease \n",
"103950 0.24 [0.18-0.3] unit decrease \n",
"103951 0.27 [0.19-0.35] unit decrease \n",
"103952 0.26 [0.18-0.34] unit decrease \n",
"103953 0.20 [0.14-0.26] unit decrease \n",
"103954 0.22 [0.16-0.28] unit decrease \n",
"103955 0.17 [0.11-0.23] unit decrease \n",
"103956 0.16 [0.1-0.22] unit decrease \n",
"103957 0.63 [0.59-0.67] unit decrease \n",
"103958 0.47 [0.39-0.55] unit increase \n",
"103959 0.24 [0.18-0.3] unit increase \n",
"103960 0.10 [0.061-0.139] unit increase \n",
"103961 0.86 [0.55-1.17] unit increase \n",
"103962 0.20 [0.14-0.26] unit decrease \n",
"103963 0.29 [0.19-0.39] unit increase \n",
"103964 0.42 [0.28-0.56] unit increase \n",
"103965 0.48 [0.34-0.62] unit increase \n",
"103966 0.40 [0.26-0.54] unit decrease \n",
"103967 0.09 [0.051-0.129] unit decrease \n",
"103968 0.42 [0.24-0.6] unit increase \n",
"\n",
" PLATFORM [SNPS PASSING QC] CNV my_index x y \n",
"0 Affymetrix, Illumina [~ 5200000] N 0 0 2015-01-08 \n",
"1 Affymetrix, Illumina [~ 5200000] N 1 1 2015-01-08 \n",
"2 Affymetrix, Illumina [~ 5200000] N 2 2 2015-01-08 \n",
"3 Affymetrix, Illumina [~ 5200000] N 3 3 2015-01-08 \n",
"4 Affymetrix, Illumina [~ 5200000] N 4 4 2015-01-08 \n",
"5 Affymetrix, Illumina [~ 5200000] N 5 5 2015-01-08 \n",
"6 Affymetrix, Illumina [~ 5200000] N 6 6 2015-01-08 \n",
"7 Affymetrix, Illumina [~ 5200000] N 7 7 2015-01-08 \n",
"8 Affymetrix, Illumina [~ 5200000] N 8 8 2015-01-08 \n",
"9 Affymetrix, Illumina [~ 5200000] N 9 9 2015-01-08 \n",
"10 Affymetrix, Illumina [~ 5200000] N 10 10 2015-01-08 \n",
"11 Affymetrix, Illumina [~ 5200000] N 11 11 2015-01-08 \n",
"12 Affymetrix, Illumina [~ 5200000] N 12 12 2015-01-08 \n",
"13 Affymetrix, Illumina [~ 5200000] N 13 13 2015-01-08 \n",
"14 Affymetrix, Illumina [~ 5200000] N 14 14 2015-01-08 \n",
"15 Affymetrix, Illumina [~ 5200000] N 15 15 2015-01-08 \n",
"16 Affymetrix, Illumina [~ 5200000] N 16 16 2015-01-08 \n",
"17 Affymetrix, Illumina [~ 5200000] N 17 17 2015-01-08 \n",
"18 Affymetrix, Illumina [~ 5200000] N 18 18 2015-01-08 \n",
"19 Affymetrix, Illumina [~ 5200000] N 19 19 2015-01-08 \n",
"20 Affymetrix, Illumina [~ 5200000] N 20 20 2015-01-08 \n",
"21 Affymetrix, Illumina [~ 5200000] N 21 21 2015-01-08 \n",
"22 Affymetrix, Illumina [~ 5200000] N 22 22 2015-01-08 \n",
"23 Affymetrix, Illumina [~ 5200000] N 23 23 2015-01-08 \n",
"24 Affymetrix, Illumina [~ 5200000] N 24 24 2015-01-08 \n",
"25 Affymetrix, Illumina [~ 5200000] N 25 25 2015-01-08 \n",
"26 Affymetrix, Illumina [~ 5200000] N 26 26 2015-01-08 \n",
"27 Affymetrix, Illumina [~ 5200000] N 27 27 2015-01-08 \n",
"28 Affymetrix, Illumina [~ 5200000] N 28 28 2015-01-08 \n",
"29 Affymetrix, Illumina [~ 5200000] N 29 29 2015-01-08 \n",
"... ... ... ... ... ... \n",
"103390 Affymetrix [629686] N 103390 103390 2018-08-22 \n",
"103391 Affymetrix [629686] N 103391 103391 2018-08-22 \n",
"103392 Affymetrix [629686] N 103392 103392 2018-08-22 \n",
"103393 Affymetrix [629686] N 103393 103393 2018-08-22 \n",
"103394 Affymetrix [629686] N 103394 103394 2018-08-22 \n",
"103395 Affymetrix [629686] N 103395 103395 2018-08-22 \n",
"103396 Affymetrix [622716] N 103396 103396 2018-08-22 \n",
"103946 Affymetrix [622716] N 103946 103946 2018-08-22 \n",
"103947 Affymetrix [622716] N 103947 103947 2018-08-22 \n",
"103948 Affymetrix [622716] N 103948 103948 2018-08-22 \n",
"103949 Affymetrix [622716] N 103949 103949 2018-08-22 \n",
"103950 Affymetrix [622716] N 103950 103950 2018-08-22 \n",
"103951 Affymetrix [622716] N 103951 103951 2018-08-22 \n",
"103952 Affymetrix [622716] N 103952 103952 2018-08-22 \n",
"103953 Affymetrix [622716] N 103953 103953 2018-08-22 \n",
"103954 Affymetrix [622716] N 103954 103954 2018-08-22 \n",
"103955 Affymetrix [622716] N 103955 103955 2018-08-22 \n",
"103956 Affymetrix [622716] N 103956 103956 2018-08-22 \n",
"103957 Affymetrix [622716] N 103957 103957 2018-08-22 \n",
"103958 Affymetrix [622716] N 103958 103958 2018-08-22 \n",
"103959 Affymetrix [622716] N 103959 103959 2018-08-22 \n",
"103960 Affymetrix [622716] N 103960 103960 2018-08-22 \n",
"103961 Affymetrix [622716] N 103961 103961 2018-08-22 \n",
"103962 Affymetrix [622716] N 103962 103962 2018-08-22 \n",
"103963 Affymetrix [622716] N 103963 103963 2018-08-22 \n",
"103964 Affymetrix [622716] N 103964 103964 2018-08-22 \n",
"103965 Affymetrix [622716] N 103965 103965 2018-08-22 \n",
"103966 Affymetrix [622716] N 103966 103966 2018-08-22 \n",
"103967 Affymetrix [622716] N 103967 103967 2018-08-22 \n",
"103968 Affymetrix [622716] N 103968 103968 2018-08-22 \n",
"\n",
"[4676 rows x 37 columns]"
]
},
"execution_count": 190,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"gwas[reduce(my_and, map(f1, ['R', 'A', 'T']))]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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