602panel_test/sample_coverage_v0_20220906.py

import sys,collections,math,os,os.path,re
import pandas as pd
from pandas.core.frame import DataFrame
import argparse





#####计算靶区间的平均测序深度
def coverage_sample(inputpath,sampleid):
	coveragedir = os.path.join(inputpath, '10Coverage')
	unfilterreadsdir = coveragedir + '/' + sampleid + '.cov.samtools.txt'
	inputdata1 = pd.read_table(unfilterreadsdir, header=None, sep='\t', low_memory=False, names=['chr', 'pos', 'reads'])
	targetdir = '/cgdata/liuxiangqiong/work62pancancer/pipeline/v0/refdata/NanOnco_Plus_Panel_v2.0_Covered_b37_cg.parY2X.sort.bed'
	targetdata = pd.read_table(targetdir, sep='\t', header=None,names=['chr', 'start', 'end', 'gene', 'infor1', 'strand'])
	samplecov = pd.DataFrame()
	for j in range(len(targetdata)):
		regionchr = targetdata.loc[j, 'chr']
		regionstart = targetdata.loc[j, 'start']
		regionend = targetdata.loc[j, 'end']
		regioninfor = inputdata1[
			(inputdata1['chr'] >= regionchr) & (inputdata1['pos'] >= regionstart) & (
					inputdata1['pos'] <= regionend)]
		if len(regioninfor)!=0:
			samplecov.loc[j, 'chr'] = targetdata.loc[j, 'chr']
			samplecov.loc[j, 'start'] = targetdata.loc[j, 'start']
			samplecov.loc[j, 'end'] = targetdata.loc[j, 'end']
			samplecov.loc[j, 'gene'] = targetdata.loc[j, 'gene']
			samplecov.loc[j, 'strand'] = targetdata.loc[j, 'strand']
			samplecov.loc[j, sampleid] = int(regioninfor['reads'].sum() / len(regioninfor))
		else:
			continue
		#print(samplecov)
	outputdir=os.path.join(coveragedir,sampleid+'.cov.samtools_coverage.txt')
	samplecov.to_csv(outputdir,sep='\t',index=False,header=True)

if __name__=='__main__':
	parser = argparse.ArgumentParser(description='coverage for probe')
	parser.add_argument('-i', '--inputpath', type=str, help='the path of lane')
	parser.add_argument('-s', '--sampleid', type=str, help='samplename')
	args = parser.parse_args()
	Inputpath = args.inputpath
	Sampelid=args.sampleid
	coverage_sample(Inputpath, Sampelid)