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oeway/BioStudies-HTTP-data-access-jupyterlite.ipynb

Last active May 12, 2022 11:49
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BioStudies-HTTP-data-access-jupyterlite.ipynb
{
"metadata": {
"kernelspec": {
"name": "python",
"display_name": "Pyolite",
"language": "python"
},
"language_info": {
"codemirror_mode": {
"name": "python",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8"
}
},
"nbformat_minor": 4,
"nbformat": 4,
"cells": [
{
"cell_type": "code",
"source": "import micropip\nawait micropip.install([\"jsonpath-ng\", \"ipyplot\"])",
"metadata": {
"trusted": true
},
"execution_count": 12,
"outputs": []
},
{
"cell_type": "code",
"source": "# import requests\nimport json\n# import urllib.request\nfrom pyodide import http\nfrom jsonpath_ng import jsonpath\nfrom jsonpath_ng.ext import parse\nfrom IPython.display import Image, display, Markdown\nimport ipyplot",
"metadata": {
"trusted": true
},
"execution_count": 3,
"outputs": []
},
{
"cell_type": "markdown",
"source": "### Get Study",
"metadata": {}
},
{
"cell_type": "code",
"source": "prefix = 'https://www.ebi.ac.uk/biostudies'\nstudy_endpoint = prefix + '/api/v1/studies/{accession}'\naccession = 'S-BIAD4'\n\n# Load the study json from the API endpoint\nurl = study_endpoint.format(accession=accession)\n\nprint ('Fetching study from {} ...'.format(url))\n\nresponse = await http.pyfetch(url)\nstudy = await response.json()\n# study = json.loads(requests.get(url).text)\nstudy_attributes = parse('$.section.attributes').find(study)[0].value\nattribute_html = list(map( lambda node: '<tr><td><b>{}</b></td><td style=\"text-align:left\">{}</td></tr>'.format(node['name'], node['value']) ,study_attributes ))\ndisplay(Markdown('<table>{}</table>'.format(\"\".join(attribute_html))))\n",
"metadata": {
"trusted": true
},
"execution_count": 5,
"outputs": [
{
"name": "stdout",
"text": "Fetching study from https://www.ebi.ac.uk/biostudies/api/v1/studies/S-BIAD4 ...\n",
"output_type": "stream"
},
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.Markdown object>",
"text/markdown": "<table><tr><td><b>Title</b></td><td style=\"text-align:left\">A 3D molecular atlas of the chick embryonic heart</td></tr><tr><td><b>Description</b></td><td style=\"text-align:left\">We present a detailed analysis of gene expression in the 2-day (HH12) embryonic chick heart. RNA-seq of 13 micro-dissected regions reveals regionalised expression of 15,570 genes. Of these, 132 were studied by in situ hybridisation and a subset (38 genes) was mapped by Optical Projection Tomography or serial sectioning to build a detailed 3-dimensional atlas of expression. We display this with a novel interactive 3-D viewer and as stacks of sections, revealing the boundaries of expression domains and regions of overlap. Analysis of the expression domains also defines some sub-regions distinct from those normally recognised by anatomical criteria at this stage of development, such as a previously undescribed subdivision of the atria into two orthogonal sets of domains (dorsoventral and left-right). We also include a detailed comparison of expression in the chick with the mouse and other species.</td></tr><tr><td><b>Study type</b></td><td style=\"text-align:left\">RNAseq</td></tr><tr><td><b>Study Organism</b></td><td style=\"text-align:left\">Gallus gallus</td></tr><tr><td><b>Number of Experiments</b></td><td style=\"text-align:left\">3</td></tr></table>"
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": "### Get Image List",
"metadata": {}
},
{
"cell_type": "code",
"source": "# This study has files outside the main JSON in a PageTab attribute is called `File List`\nfilelists = parse('$..attributes[?(@.name == \"File List\")]').find(study)\n# We will display some images from the first file list here\n# Set the caption to the description of the parent section \ndescription_node = next( filter(lambda node: node['name']=='Description', filelists[0].context.value))\ncaption = description_node['value']\nprint (caption)",
"metadata": {
"trusted": true
},
"execution_count": 7,
"outputs": [
{
"name": "stdout",
"text": "Histological sections of 40 markers as registered stacks of images\n",
"output_type": "stream"
}
]
},
{
"cell_type": "markdown",
"source": "#### Get Image Paths",
"metadata": {}
},
{
"cell_type": "code",
"source": "filename = filelists[0].value['value'] + '.json' \nfile_endpoint = prefix + '/files/{accession}/{filename}'\nurl = file_endpoint.format(accession=accession, filename = filename)\nprint ('Fetching file list from {}...'.format(url))\n# filelist = json.loads(requests.get(url).text)\nresponse = await http.pyfetch(url)\nfilelist = await response.json()\nprint ('Got {} files'.format( parse('@.`len`').find( filelist)[0].value))",
"metadata": {
"trusted": true
},
"execution_count": 9,
"outputs": [
{
"name": "stdout",
"text": "Fetching file list from https://www.ebi.ac.uk/biostudies/files/S-BIAD4/HistologicalSections-LibFile.json...\nGot 2418 files\n",
"output_type": "stream"
}
]
},
{
"cell_type": "markdown",
"source": "#### Display Images",
"metadata": {}
},
{
"cell_type": "code",
"source": "# Display first 9 images\nimage_nodes = parse('@[0:9]').find(filelist)\nimages = []\nlabels = []\nfor node in image_nodes: \n images.append(file_endpoint.format(accession=accession, filename = node.value['path']))\n labels.append( '{} bytes'.format(node.value['size']))\nipyplot.plot_images(images,labels,img_width=300)",
"metadata": {
"trusted": true
},
"execution_count": 10,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": "<IPython.core.display.HTML object>",
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word-wrap: break-word;\">723020 bytes</h4>\n <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-040.jpg</h4><img src=\"https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-040.jpg\"/>\n <a href=\"#!\">\n <span class=\"ipyplot-img-close\"/>\n </a>\n <a href=\"#ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-dkTdf79cKAyohUQACNyL3A\">\n <span class=\"ipyplot-img-expand\"/>\n </a>\n </div>\n </div>\n \n <div class=\"ipyplot-placeholder-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <div id=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-5HSE3Romaff3mkhpcLuaqi\" class=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <h4 style=\"font-size: 12px; word-wrap: break-word;\">770692 bytes</h4>\n <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-041.jpg</h4><img src=\"https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-041.jpg\"/>\n <a href=\"#!\">\n <span class=\"ipyplot-img-close\"/>\n </a>\n <a href=\"#ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-5HSE3Romaff3mkhpcLuaqi\">\n <span class=\"ipyplot-img-expand\"/>\n </a>\n </div>\n </div>\n \n <div class=\"ipyplot-placeholder-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <div id=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-hys4a4NYVTa7cuzCps4iRb\" class=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <h4 style=\"font-size: 12px; word-wrap: break-word;\">797758 bytes</h4>\n <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-042.jpg</h4><img src=\"https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-042.jpg\"/>\n <a href=\"#!\">\n <span class=\"ipyplot-img-close\"/>\n </a>\n <a href=\"#ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-hys4a4NYVTa7cuzCps4iRb\">\n <span class=\"ipyplot-img-expand\"/>\n </a>\n </div>\n </div>\n \n <div class=\"ipyplot-placeholder-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <div id=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-NtYqvma596F8rmMtkGv524\" class=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <h4 style=\"font-size: 12px; word-wrap: break-word;\">832930 bytes</h4>\n <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-043.jpg</h4><img src=\"https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-043.jpg\"/>\n <a href=\"#!\">\n <span class=\"ipyplot-img-close\"/>\n </a>\n <a href=\"#ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-NtYqvma596F8rmMtkGv524\">\n <span class=\"ipyplot-img-expand\"/>\n </a>\n </div>\n </div>\n \n <div class=\"ipyplot-placeholder-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <div id=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-GhB5VJFT8BqY8btmdAzSpG\" class=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <h4 style=\"font-size: 12px; 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word-wrap: break-word;\">791507 bytes</h4>\n <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-046.jpg</h4><img src=\"https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-046.jpg\"/>\n <a href=\"#!\">\n <span class=\"ipyplot-img-close\"/>\n </a>\n <a href=\"#ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-JuBgbeg2iozRRP6Ng7Kmji\">\n <span class=\"ipyplot-img-expand\"/>\n </a>\n </div>\n </div>\n \n <div class=\"ipyplot-placeholder-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <div id=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-4X8Q9MjhRS9BEtoNErzr9D\" class=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <h4 style=\"font-size: 12px; word-wrap: break-word;\">779908 bytes</h4>\n <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-047.jpg</h4><img src=\"https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-047.jpg\"/>\n <a href=\"#!\">\n <span class=\"ipyplot-img-close\"/>\n </a>\n <a href=\"#ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-4X8Q9MjhRS9BEtoNErzr9D\">\n <span class=\"ipyplot-img-expand\"/>\n </a>\n </div>\n </div>\n \n <div class=\"ipyplot-placeholder-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <div id=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-UTVHXU8eh44ACYo5huxGGN\" class=\"ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS\">\n <h4 style=\"font-size: 12px; word-wrap: break-word;\">777917 bytes</h4>\n <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-048.jpg</h4><img src=\"https://www.ebi.ac.uk/biostudies/files/S-BIAD4/S-BIAD4/Histological-Sections/ADAMTS3/ADAMTS3-048.jpg\"/>\n <a href=\"#!\">\n <span class=\"ipyplot-img-close\"/>\n </a>\n <a href=\"#ipyplot-content-div-mRNZiYVe2oGFcmkLDWhsQS-UTVHXU8eh44ACYo5huxGGN\">\n <span class=\"ipyplot-img-expand\"/>\n </a>\n </div>\n </div>\n </div>\n </textarea>\n </div>\n "
},
"metadata": {}
},
{
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