コード例 #1
0
ファイル: main.py プロジェクト: ksahlin/GetDistr
def main_pipline(args,param):
	"""
		Algorithm a follows:
			1 Filter bam file to only consider interesting reads
			2 Estimate library parameters (lib_est) and print to library_info.txt.
				(mu, sigam, adjusted mu, sigma, ESS etc.)
			3 Parse bamfile and get mean and stddev over each position in assembly (get_bp_stats)
				Print to bp_stats.csv
			4 Get gap coordinates in assembly (get_gap_coordinates)
				print to gap_coordinates.csv 
			5 Calculate pvalues based on expected span mean and stddev (calc_pvalues)
				print ctg_accesion, pos, pvalues to p_values.csv
			5' Cluster p-values into significant cliques and print significant
				locations on GFF format.


	"""

	if not os.path.exists(args.outfolder):
		os.makedirs(args.outfolder)

	# 1
	bam_out = os.path.join(args.outfolder,'bam_filtered.bam')
	filter_bamfile(args,param)

	# 2
	lib_est.LibrarySampler(bam_out,param)
 
	# 3
	collect_libstats(args,args.outfolder,param)
	get_bp_stats.parse_bam(bam_out, param)

	# 4
	#get_gap_coordinates.
	gap_coordinates(args,param)

	# 5-5' 
	# sample_file_path = os.path.join(args.outfolder,'sample_se.txt')
	# sample_ess_correction.main(sample_file_path, param)
	p_value_cluster(args,param)
コード例 #2
0
ファイル: main.py プロジェクト: ksahlin/GetDistr
def bp_stats(args,param):
	bam_in = os.path.join(args.outfolder,'bam_filtered.bam')
	collect_libstats(args,args.outfolder, param)
	get_bp_stats.parse_bam(bam_in, param)