Mercurial > repos > estrain > srst2

comparison scoreProfiles.py @ 0:efc202baae1f draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload
author estrain
date Sun, 03 Dec 2017 13:28:11 -0500
parents
children
comparison
equal deleted inserted replaced
-1:000000000000 0:efc202baae1f
1 #!/usr/bin/env
2
3 ## Generate basic summary stats for SRST2 (v2) allele score output. Generate summaries for each profile defined in the database
4 ## author: errol strain, estrain@gmail.com
5
6 from argparse import (ArgumentParser, FileType)
7 import sys
8 import glob
9 from decimal import Decimal
10
11 def parse_args():
12 "Parse the input arguments, use '-h' for help."
13
14 parser = ArgumentParser(description='Generate Summary Scores for SRST2 Allele Score Output')
15
16 # Read inputs
17 parser.add_argument('--mlst_definitions', type=str, required=True, nargs=1, help='MLST Definitions')
18 parser.add_argument('--output', type=str, required=True, nargs=1, help='MLST Definitions')
19 parser.add_argument('--profile_cov', type=str, required=False, help='Minimum Average Coverage to Report ST Profile',default="98")
20 parser.add_argument('--profile_max_mismatch', type=str, required=False, help='Maximum Number of Mismatches (SNPs)', default="1")
21
22 return parser.parse_args()
23
24 args =parse_args()
25
26 allHash = {}
27
28 # Read in Profile Database
29 profiles = open(args.mlst_definitions[0],"r")
30 output = open(args.output[0],"w")
31
32 # Minimum mean percent coverage for reporting profile
33 min_per=float(args.profile_cov)
34 # Maximum mean mismatch for reporting profile
35 max_mis=float(args.profile_max_mismatch)
36
37 # Read in Allele Scores
38 # Scores should be in srts2*.scores file
39 # Column 0:Allele, 1:Score, 2:Avg Depth, 5:% Coverage, 7:Mismatches, 8:Indels
40 scoreFile = open(glob.glob("srst2*.scores")[0],"r")
41 scoreFile.readline()
42
43 for line in scoreFile.readlines() :
44 els = line.split("\t")
45 vals = els[0].split("_")
46 allHash.update({els[0]:line})
47
48
49 # Allele names in first row
50 als = profiles.readline().rstrip()
51 filehead = als + str("\tMean_Score\tMean_Depth\tMean_%_Coverage\tTotal_Mismatches\tTotal_Indels\n")
52 output.write(filehead)
53
54 genes = als.split("\t")
55
56 for line in profiles.readlines() :
57 line = line.rstrip()
58 els = line.split("\t")
59 alleles = []
60 for i in range(1,len(genes)) :
61 alleles.append(genes[i] + "_" + els[i])
62 mscore=0
63 mdepth=0
64 mcover=0
65 mmisma=0
66 mindel=0
67 for i in alleles :
68 if i in allHash :
69 vals=str(allHash[i]).split("\t")
70 mscore+=float(vals[1])
71 mdepth+=float(vals[2])
72 mcover+=float(vals[5])
73 mmisma+=int(vals[7])
74 mindel+=int(vals[8])
75
76 mscore=round(Decimal(mscore/(len(genes)-1)),5)
77 mdepth=round(Decimal(mdepth/(len(genes)-1)),2)
78 mcover=round(Decimal(mcover/(len(genes)-1)),2)
79
80 if mmisma<=max_mis and mcover>=min_per :
81 output.write(line + "\t" + str(mscore) + "\t" + str(mdepth) + "\t" + str(mcover) + "\t" + str(mmisma) + "\t" + str(mindel) + "\n")
82