|
0
|
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("--summ", help="The 1_Summary file from the imgt output")
|
|
|
17 parser.add_argument("--aa", help="The 5_AA-Sequence file from the imgt output")
|
|
|
18 parser.add_argument("--junction", help="The 6_Junction file from the imgt output")
|
|
|
19 parser.add_argument("--output", help="Output file")
|
|
|
20
|
|
|
21 args = parser.parse_args()
|
|
|
22
|
|
|
23 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']
|
|
|
24 old_sequence_columns = [u'CDR1-IMGT', u'CDR2-IMGT', u'CDR3-IMGT']
|
|
|
25 old_junction_columns = [u'JUNCTION']
|
|
|
26
|
|
|
27 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']
|
|
|
28 added_sequence_columns = [u'FR1-IMGT', u'FR2-IMGT', u'FR3-IMGT', u'CDR3-IMGT', u'JUNCTION', u'J-REGION', u'FR4-IMGT']
|
|
|
29 added_junction_columns = [u"P3'V-nt nb", u'N-REGION-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",
|
|
|
30 u"5'D-REGION trimmed-nt nb", u"3'D-REGION trimmed-nt nb", u"5'J-REGION trimmed-nt nb", u"N-REGION", u"N1-REGION", u"N2-REGION"]
|
|
|
31
|
|
|
32 outFile = args.output
|
|
|
33
|
|
|
34 #fSummary = pd.read_csv(triplets[0][0], sep="\t", low_memory=False)
|
|
|
35 fSummary = pd.read_csv(args.summ, sep="\t", dtype=object)
|
|
|
36 #fSequence = pd.read_csv(triplets[0][1], sep="\t", low_memory=False)
|
|
|
37 fSequence = pd.read_csv(args.aa, sep="\t", dtype=object)
|
|
|
38 #fJunction = pd.read_csv(triplets[0][2], sep="\t", low_memory=False)
|
|
|
39 fJunction = pd.read_csv(args.junction, sep="\t", dtype=object)
|
|
|
40 tmp = fSummary[["Sequence ID", "JUNCTION frame", "V-GENE and allele", "D-GENE and allele", "J-GENE and allele"]]
|
|
|
41
|
|
|
42 tmp["CDR1 Seq"] = fSequence["CDR1-IMGT"]
|
|
|
43 tmp["CDR1 Length"] = fSummary["CDR1-IMGT length"]
|
|
|
44
|
|
|
45 tmp["CDR2 Seq"] = fSequence["CDR2-IMGT"]
|
|
|
46 tmp["CDR2 Length"] = fSummary["CDR2-IMGT length"]
|
|
|
47
|
|
|
48 tmp["CDR3 Seq"] = fSequence["CDR3-IMGT"]
|
|
|
49 tmp["CDR3 Length"] = fSummary["CDR3-IMGT length"]
|
|
|
50
|
|
|
51 tmp["CDR3 Seq DNA"] = fJunction["JUNCTION"]
|
|
|
52 tmp["CDR3 Length DNA"] = '1'
|
|
|
53 tmp["Strand"] = fSummary["Orientation"]
|
|
|
54 tmp["CDR3 Found How"] = 'a'
|
|
|
55
|
|
|
56 for col in added_summary_columns:
|
|
|
57 tmp[col] = fSummary[col]
|
|
|
58
|
|
|
59 for col in added_sequence_columns:
|
|
|
60 tmp[col] = fSequence[col]
|
|
|
61
|
|
|
62 for col in added_junction_columns:
|
|
|
63 tmp[col] = fJunction[col]
|
|
|
64
|
|
|
65 outFrame = tmp
|
|
|
66
|
|
|
67 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',
|
|
|
68 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',
|
|
|
69 'AA JUNCTION', 'Functionality comment', 'Sequence', 'FR1-IMGT', 'FR2-IMGT', 'FR3-IMGT', 'CDR3-IMGT', 'JUNCTION', 'J-REGION', 'FR4-IMGT', 'P3V-nt nb',
|
|
|
70 'N-REGION-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',
|
|
|
71 '5J-REGION trimmed-nt nb', "N-REGION", "N1-REGION", "N2-REGION"]
|
|
|
72
|
|
|
73 """
|
|
|
74 IGHV[0-9]-[0-9ab]+-?[0-9]?D?
|
|
|
75 TRBV[0-9]{1,2}-?[0-9]?-?[123]?
|
|
|
76 IGKV[0-3]D?-[0-9]{1,2}
|
|
|
77 IGLV[0-9]-[0-9]{1,2}
|
|
|
78 TRAV[0-9]{1,2}(-[1-46])?(/DV[45678])?
|
|
|
79 TRGV[234589]
|
|
|
80 TRDV[1-3]
|
|
|
81
|
|
|
82 IGHD[0-9]-[0-9ab]+
|
|
|
83 TRBD[12]
|
|
|
84 TRDD[1-3]
|
|
|
85
|
|
|
86 IGHJ[1-6]
|
|
|
87 TRBJ[12]-[1-7]
|
|
|
88 IGKJ[1-5]
|
|
|
89 IGLJ[12367]
|
|
|
90 TRAJ[0-9]{1,2}
|
|
|
91 TRGJP?[12]
|
|
|
92 TRDJ[1-4]
|
|
|
93 """
|
|
|
94
|
|
|
95 vPattern = [r"(IGHV[0-9]-[0-9ab]+-?[0-9]?D?)",
|
|
|
96 r"(TRBV[0-9]{1,2}-?[0-9]?-?[123]?)",
|
|
|
97 r"(IGKV[0-3]D?-[0-9]{1,2})",
|
|
|
98 r"(IGLV[0-9]-[0-9]{1,2})",
|
|
|
99 r"(TRAV[0-9]{1,2}(-[1-46])?(/DV[45678])?)",
|
|
|
100 r"(TRGV[234589])",
|
|
|
101 r"(TRDV[1-3])",
|
|
|
102 r"(IGHV[0-9]S[0-9]+)"]
|
|
|
103
|
|
|
104 dPattern = [r"(IGHD[0-9]-[0-9ab]+)",
|
|
|
105 r"(TRBD[12])",
|
|
|
106 r"(TRDD[1-3])"]
|
|
|
107
|
|
|
108 jPattern = [r"(IGHJ[1-6])",
|
|
|
109 r"(TRBJ[12]-[1-7])",
|
|
|
110 r"(IGKJ[1-5])",
|
|
|
111 r"(IGLJ[12367])",
|
|
|
112 r"(TRAJ[0-9]{1,2})",
|
|
|
113 r"(TRGJP?[12])",
|
|
|
114 r"(TRDJ[1-4])"]
|
|
|
115
|
|
|
116 vPattern = re.compile(r"|".join(vPattern))
|
|
|
117
|
|
|
118 dPattern = re.compile(r"|".join(dPattern))
|
|
|
119
|
|
|
120 jPattern = re.compile(r"|".join(jPattern))
|
|
|
121
|
|
|
122
|
|
|
123 def filterGenes(s, pattern):
|
|
|
124 if type(s) is not str:
|
|
|
125 return "NA"
|
|
|
126 res = pattern.search(s)
|
|
|
127 if res:
|
|
|
128 return res.group(0)
|
|
|
129 return "NA"
|
|
|
130
|
|
|
131
|
|
|
132
|
|
|
133 outFrame["Top V Gene"] = outFrame["Top V Gene"].apply(lambda x: filterGenes(x, vPattern))
|
|
|
134 outFrame["Top D Gene"] = outFrame["Top D Gene"].apply(lambda x: filterGenes(x, dPattern))
|
|
|
135 outFrame["Top J Gene"] = outFrame["Top J Gene"].apply(lambda x: filterGenes(x, jPattern))
|
|
|
136
|
|
|
137
|
|
|
138 tmp = outFrame["VDJ Frame"]
|
|
|
139 tmp = tmp.replace("in-frame", "In-frame")
|
|
|
140 tmp = tmp.replace("null", "Out-of-frame")
|
|
|
141 tmp = tmp.replace("out-of-frame", "Out-of-frame")
|
|
|
142 outFrame["VDJ Frame"] = tmp
|
|
|
143 outFrame["CDR3 Length DNA"] = outFrame["CDR3 Seq DNA"].map(str).map(len)
|
|
|
144 safeLength = lambda x: len(x) if type(x) == str else 0
|
|
|
145 #outFrame = outFrame[(outFrame["CDR3 Seq DNA"].map(safeLength) > 0) & (outFrame["Top V Gene"] != "NA") & (outFrame["Top J Gene"] != "NA")] #filter out weird rows?
|
|
|
146 #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?
|
|
|
147 outFrame.to_csv(outFile, sep="\t", index=False, index_label="index")
|
