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@KaiSmith
Last active December 18, 2015 10:29
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IPython Notebook tutorial for using genda: Chi-Squared Association Test Viewable at http://nbviewer.ipython.org/be0590cd0cb37cc58a96
{
"metadata": {
"name": "genda - Chi2_association"
},
"nbformat": 2,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": true,
"input": [
"from genda.formats import Genotype as G",
"import matplotlib.pyplot as plt",
"import pandas as pd",
"import numpy as np"
],
"language": "python",
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Load in my saved data",
"#In thi example case and control are just data frames with data",
"control = pd.load('tests/data/control_example')",
"case = pd.load('tests/data/case_example')",
"encoder = pd.load('tests/data/encoder_example')"
],
"language": "python",
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"#Applying the encoder",
"#If your data has already had an encoder applied to it, don't worry about this step",
"#Also, if your data is a SNP_array object, this process is simplified by the SNP_array.apply_encoder function",
"from genda.formats.Snp_array import _single_column_allele",
"case = case.ix[encoder.index,:]",
"control = control.ix[encoder.index,:]",
"case.geno = case.apply(_single_column_allele, encoder = encoder, axis = 1)",
"control.geno = control.apply(_single_column_allele, encoder = encoder, axis = 1)"
],
"language": "python",
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Removes rows so the indexes are identicle and ready to analyze",
"case.geno, control.geno = G.comparable(case.geno, control.geno)"
],
"language": "python",
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"#Perform association test",
"p = G.chi2_association(control.geno,case.geno)"
],
"language": "python",
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Graph results",
"plt.scatter(range(len(p[1])), -1*np.log10(p[1]))"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 6,
"text": [
"<matplotlib.collections.PathCollection at 0x8794590>"
]
},
{
"output_type": "display_data",
"png": 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VKufUqe8jNXUWgD4AHsbFi8Mwa9acCpVB8e/k+++/R0hINCwWB5o0aY9jx465WyRFOVNq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\nAAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"#Check value of a certain SNP",
"p[0]['rs12913832']"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 7,
"text": [
"9.581070982428592e-09"
]
}
],
"prompt_number": 7
}
]
}
]
}
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