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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 36, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"Total Truth VCF records: 4358\n", | ||
"Non-reference VCF records: 4358\n", | ||
"Total Query VCF records: 7494\n", | ||
"Non-reference VCF records: 4495\n" | ||
] | ||
}, | ||
{ | ||
"name": "stderr", | ||
"output_type": "stream", | ||
"text": [ | ||
"/anaconda3/lib/python3.6/site-packages/allel/io/vcf_read.py:1741: UserWarning: invalid INFO header: '##INFO=<ID=VDB,Number=1,Type=Float,Description=\"Variant Distance Bias for filtering splice-site artefacts in RNA-seq data (bigger is better)\",Version=\"3\">\\n'\n", | ||
" warnings.warn('invalid INFO header: %r' % header)\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"#!/usr/local/bin python\n", | ||
"import sys\n", | ||
"import pandas as pd\n", | ||
"import allel #pip install scikit-allel to install this module for analysis of large scale genetic variation data\n", | ||
"import csv\n", | ||
"\n", | ||
"golden_vcf = allel.vcf_to_dataframe(\"bcftools_variants.vcf\", ['variants/CHROM', 'variants/POS', 'variants/REF', 'variants/ALT', 'QUAL'], alt_number=1) # Storing the information in the VCF file into a dataframe\n", | ||
"query_vcf = allel.vcf_to_dataframe(\"freeebayes_variants.vcf\", ['variants/CHROM', 'variants/POS', 'variants/REF', 'variants/ALT', 'QUAL'], alt_number=1)\n", | ||
"golden_variants_list = golden_vcf.values.tolist() #Each variant info will be saved onto a list, creating a list of list\n", | ||
"query_variants_list = query_vcf.values.tolist()\n", | ||
"\n", | ||
"# for list in query_variants_list:\n", | ||
"# print (list[4])\n", | ||
"\n", | ||
"header = ['TRUTH.TOTAL', 'TP', 'FP', 'FN', 'QUERY.TOTAL', 'Recall', 'Precision']\n", | ||
"list = []\n", | ||
"\n", | ||
"#Totals\n", | ||
"Truth_Total = len(golden_variants_list)\n", | ||
"print (\"Total Truth VCF records: \" + str(Truth_Total))\n", | ||
"Truth_Pass_Total = len([x for x in golden_variants_list if x[4] > 2])\n", | ||
"print (\"Non-reference VCF records: \" + str(Truth_Pass_Total))\n", | ||
"Query_Total = len(query_variants_list)\n", | ||
"print (\"Total Query VCF records: \" + str(Query_Total))\n", | ||
"Query_Pass_Total = len([x for x in query_variants_list if x[4] > 0.003])\n", | ||
"print (\"Non-reference VCF records: \" + str(Query_Pass_Total))" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 20, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"4\n", | ||
"4\n", | ||
"5\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"a = [[1, 3, 4], [2, 4, 4], [3, 4, 5]]\n", | ||
"for list in a:\n", | ||
" print (list[2])" | ||
] | ||
}, | ||
{ | ||
"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": "3.6.5" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 2 | ||
} |