Mercurial > repos > davidvanzessen > complete_immunerepertoire_igg

comparison imgtconvert.py @ 0:7d97fa9a0423 draft

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author davidvanzessen
date Fri, 09 May 2014 09:35:32 -0400
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children 24d5d9120d93
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-1:000000000000 0:7d97fa9a0423
1 import pandas as pd
2 try:
3 pd.options.mode.chained_assignment = None # default='warn'
4 except:
5 pass
6 import re
7 import argparse
8 import os
9
10 def stop_err( msg, ret=1 ):
11 sys.stderr.write( msg )
12 sys.exit( ret )
13
14 #docs.python.org/dev/library/argparse.html
15 parser = argparse.ArgumentParser()
16 parser.add_argument("--input", help="Input folder with files")
17 parser.add_argument("--output", help="Output file")
18
19 args = parser.parse_args()
20
21 old_summary_columns = [u'Sequence ID', u'JUNCTION frame', u'V-GENE and allele', u'D-GENE and allele', u'J-GENE and allele', u'CDR1-IMGT length', u'CDR2-IMGT length', u'CDR3-IMGT length', u'Orientation']
22 old_sequence_columns = [u'CDR1-IMGT', u'CDR2-IMGT', u'CDR3-IMGT']
23 old_junction_columns = [u'JUNCTION']
24
25 added_summary_columns = [u'Functionality', u'V-REGION identity %', u'V-REGION identity nt', u'D-REGION reading frame', u'AA JUNCTION', u'Functionality comment', u'Sequence']
26 added_sequence_columns = [u'FR1-IMGT', u'FR2-IMGT', u'FR3-IMGT', u'CDR3-IMGT', u'JUNCTION', u'J-REGION', u'FR4-IMGT']
27 added_junction_columns = [u"P3'V-nt nb", u'N1-REGION-nt nb', u"P5'D-nt nb", u"P3'D-nt nb", u'N2-REGION-nt nb', u"P5'J-nt nb", u"3'V-REGION trimmed-nt nb", u"5'D-REGION trimmed-nt nb", u"3'D-REGION trimmed-nt nb", u"5'J-REGION trimmed-nt nb"]
28
29 inputFolder = args.input
30
31 dirContents = os.listdir(inputFolder)
32 if len(dirContents) == 1:
33 inputFolder = os.path.join(inputFolder, dirContents[0])
34 if os.path.isdir(inputFolder):
35 print "is dir"
36 dirContents = os.listdir(inputFolder)
37 files = sorted([os.path.join(inputFolder, f) for f in dirContents])
38
39 if len(files) % 3 is not 0:
40 stop_err("Files in zip not a multiple of 3, it should contain the all the 1_, 5_ and 6_ files for a sample")
41 import sys
42 sys.exit()
43
44 triplets = []
45 step = len(files) / 3
46 for i in range(0, step):
47 triplets.append((files[i], files[i + step], files[i + step + step]))
48
49 outFile = args.output
50
51 fSummary = pd.read_csv(triplets[0][0], sep="\t")
52 fSequence = pd.read_csv(triplets[0][1], sep="\t")
53 fJunction = pd.read_csv(triplets[0][2], sep="\t")
54 tmp = fSummary[["Sequence ID", "JUNCTION frame", "V-GENE and allele", "D-GENE and allele", "J-GENE and allele"]]
55
56 tmp["CDR1 Seq"] = fSequence["CDR1-IMGT"]
57 tmp["CDR1 Length"] = fSummary["CDR1-IMGT length"]
58
59 tmp["CDR2 Seq"] = fSequence["CDR2-IMGT"]
60 tmp["CDR2 Length"] = fSummary["CDR2-IMGT length"]
61
62 tmp["CDR3 Seq"] = fSequence["CDR3-IMGT"]
63 tmp["CDR3 Length"] = fSummary["CDR3-IMGT length"]
64
65 tmp["CDR3 Seq DNA"] = fJunction["JUNCTION"]
66 tmp["CDR3 Length DNA"] = '1'
67 tmp["Strand"] = fSummary["Orientation"]
68 tmp["CDR3 Found How"] = 'a'
69
70 for col in added_summary_columns:
71 tmp[col] = fSummary[col]
72
73 for col in added_sequence_columns:
74 tmp[col] = fSequence[col]
75
76 for col in added_junction_columns:
77 tmp[col] = fJunction[col]
78
79 outFrame = tmp
80
81 for triple in triplets[1:]:
82 fSummary = pd.read_csv(triple[0], sep="\t")
83 fSequence = pd.read_csv(triple[1], sep="\t")
84 fJunction = pd.read_csv(triple[2], sep="\t")
85
86 tmp = fSummary[["Sequence ID", "JUNCTION frame", "V-GENE and allele", "D-GENE and allele", "J-GENE and allele"]]
87
88 tmp["CDR1 Seq"] = fSequence["CDR1-IMGT"]
89 tmp["CDR1 Length"] = fSummary["CDR1-IMGT length"]
90
91 tmp["CDR2 Seq"] = fSequence["CDR2-IMGT"]
92 tmp["CDR2 Length"] = fSummary["CDR2-IMGT length"]
93
94 tmp["CDR3 Seq"] = fSequence["CDR3-IMGT"]
95 tmp["CDR3 Length"] = fSummary["CDR3-IMGT length"]
96
97 tmp["CDR3 Seq DNA"] = fJunction["JUNCTION"]
98 tmp["CDR3 Length DNA"] = '1'
99 tmp["Strand"] = fSummary["Orientation"]
100 tmp["CDR3 Found How"] = 'a'
101
102 for col in added_summary_columns:
103 tmp[col] = fSummary[col]
104
105 for col in added_sequence_columns:
106 tmp[col] = fSequence[col]
107
108 for col in added_junction_columns:
109 tmp[col] = fJunction[col]
110
111 outFrame = outFrame.append(tmp)
112
113 outFrame.columns = [u'ID', u'VDJ Frame', u'Top V Gene', u'Top D Gene', u'Top J Gene', u'CDR1 Seq', u'CDR1 Length', u'CDR2 Seq', u'CDR2 Length', u'CDR3 Seq', u'CDR3 Length', u'CDR3 Seq DNA', u'CDR3 Length DNA', u'Strand', u'CDR3 Found How', u'Functionality', 'V-REGION identity %', 'V-REGION identity nt', 'D-REGION reading frame', 'AA JUNCTION', 'Functionality comment', 'Sequence', 'FR1-IMGT', 'FR2-IMGT', 'FR3-IMGT', 'CDR3-IMGT', 'JUNCTION', 'J-REGION', 'FR4-IMGT', 'P3V-nt nb', 'N1-REGION-nt nb', 'P5D-nt nb', 'P3D-nt nb', 'N2-REGION-nt nb', 'P5J-nt nb', '3V-REGION trimmed-nt nb', '5D-REGION trimmed-nt nb', '3D-REGION trimmed-nt nb', '5J-REGION trimmed-nt nb']
114
115 vPattern = re.compile(r"IGHV[1-9]-[0-9ab]+-?[1-9]?")
116 dPattern = re.compile(r"IGHD[1-9]-[0-9ab]+")
117 jPattern = re.compile(r"IGHJ[1-9]")
118
119 def filterGenes(s, pattern):
120 if type(s) is not str:
121 return "NA"
122 res = pattern.search(s)
123 if res:
124 return res.group(0)
125 return "NA"
126
127
128 outFrame["Top V Gene"] = outFrame["Top V Gene"].apply(lambda x: filterGenes(x, vPattern))
129 outFrame["Top D Gene"] = outFrame["Top D Gene"].apply(lambda x: filterGenes(x, dPattern))
130 outFrame["Top J Gene"] = outFrame["Top J Gene"].apply(lambda x: filterGenes(x, jPattern))
131
132
133
134 tmp = outFrame["VDJ Frame"]
135 tmp = tmp.replace("in-frame", "In-frame")
136 tmp = tmp.replace("null", "Out-of-frame")
137 tmp = tmp.replace("out-of-frame", "Out-of-frame")
138 outFrame["VDJ Frame"] = tmp
139 outFrame["CDR3 Length DNA"] = outFrame["CDR3 Seq DNA"].map(str).map(len)
140 safeLength = lambda x: len(x) if type(x) == str else 0
141 outFrame = outFrame[(outFrame["CDR3 Seq DNA"].map(safeLength) > 0) & (outFrame["Top V Gene"] != "NA") & (outFrame["Top D Gene"] != "NA") & (outFrame["Top J Gene"] != "NA")] #filter out weird rows?
142 outFrame.to_csv(outFile, sep="\t", index=False, index_label="index")