Mercurial > repos > artbio > small_read_size_histograms

comparison size_histogram.py @ 0:234b83159ea8 draft

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planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/small_read_size_histograms commit ab983b2e57321e8913bd4d5f8fc89c3223c69869
author artbio
date Tue, 11 Jul 2017 11:44:36 -0400
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-1:000000000000 0:234b83159ea8
1 #!/usr/bin/python
2 # python parser module for size distributions, guided by GFF3
3
4 import argparse
5 import subprocess
6 from collections import OrderedDict
7 from smRtools import extractsubinstance
8 from smRtools import HandleSmRNAwindows
9
10
11 def Parser():
12 the_parser = argparse.ArgumentParser()
13 the_parser.add_argument('--output_size_distribution', action="store", type=str, help="size distribution dataframe")
14 the_parser.add_argument('--reference_fasta', action="store", type=str, help="output file")
15 the_parser.add_argument('--reference_bowtie_index',action='store', help="paths to indexed or fasta references")
16 the_parser.add_argument('--input',nargs='+', help="paths to multiple input files")
17 the_parser.add_argument('--ext',nargs='+', help="input file type")
18 the_parser.add_argument('--label',nargs='+', help="labels of multiple input files")
19 the_parser.add_argument('--normalization_factor',nargs='+', type=float, help="Normalization factor for input file")
20 the_parser.add_argument('--gff', type=str, help="GFF containing regions of interest")
21 the_parser.add_argument('--minquery', type=int, help="Minimum readsize")
22 the_parser.add_argument('--maxquery', type=int, help="Maximum readsize")
23 the_parser.add_argument('--global_size', action="store_true", help="if specified, size distribution is calculated for the sum of all items")
24 the_parser.add_argument('--collapse', action="store_true", help="if specified, forward and reverse reads are collapsed")
25 args = the_parser.parse_args()
26 return args
27
28
29 args=Parser()
30 if args.reference_fasta:
31 genomeRefFormat = "fastaSource"
32 genomeRefFile = args.reference_fasta
33 if args.reference_bowtie_index:
34 genomeRefFormat = "bowtieIndex"
35 genomeRefFile = args.reference_bowtie_index
36 size_distribution_file=args.output_size_distribution
37 minquery=args.minquery
38 maxquery=args.maxquery
39 filePath=args.input
40 fileExt=args.ext
41 fileLabel=args.label
42 normalization_factor=args.normalization_factor
43 global_size=args.global_size
44 collapse=args.collapse
45
46 if collapse:
47 pol=["both"]
48 else:
49 pol=["F", "R"]
50
51 MasterListOfGenomes = OrderedDict()
52
53 def process_samples(filePath):
54 for i, filePath in enumerate(filePath):
55 norm=normalization_factor[i]
56 print fileLabel[i]
57 MasterListOfGenomes[fileLabel[i]] = HandleSmRNAwindows (alignmentFile=filePath, alignmentFileFormat=fileExt[i], genomeRefFile=genomeRefFile, genomeRefFormat=genomeRefFormat,\
58 biosample=fileLabel[i], size_inf=minquery, size_sup=maxquery, norm=norm)
59 return MasterListOfGenomes
60
61
62 def write_size_distribution_dataframe(readDict, size_distribution_file, pol=["both"] ):
63 '''refactored on 7-9-2014'''
64 with open(size_distribution_file, 'w') as size_distrib:
65 print >>size_distrib, "gene\tpolarity\tsize\tcount\tsample"
66 for sample in readDict.keys():
67 if args.gff:
68 dict=readDict[sample]
69 else:
70 dict=readDict[sample].instanceDict
71 for gene in dict.keys():
72 histogram = dict[gene].size_histogram()
73 for polarity in pol:
74 for size, count in histogram[polarity].iteritems():
75 print >>size_distrib, "%s\t%s\t%s\t%s\t%s" % (gene, polarity, size, count, sample)
76
77
78 def write_size_distribution_dataframe_global(readDict, size_distribution_file, pol=["both"]):
79 with open(size_distribution_file, 'w') as size_distrib:
80 print >>size_distrib, "gene\tpolarity\tsize\tcount\tsample"
81 for sample in readDict.keys():
82 histogram = readDict[sample].size_histogram()
83 gene="sample"
84 for polarity in pol:
85 for size, count in histogram[polarity].iteritems():
86 print >>size_distrib, "%s\t%s\t%s\t%s\t%s" % (gene, polarity, size, count, sample)
87
88
89 def gff_item_subinstances(readDict, gff3):
90 GFFinstanceDict=OrderedDict()
91 with open(gff3) as gff:
92 for line in gff:
93 if line[0] == "#": continue
94 gff_fields = line[:-1].split("\t")
95 chrom = gff_fields[0]
96 gff_name = gff_fields[-1].split("Name=")[-1].split(";")[0] # to isolate the GFF Name
97 item_upstream_coordinate = int(gff_fields[3])
98 item_downstream_coordinate = int(gff_fields[4])
99 item_polarity = gff_fields[6]
100 for sample in readDict.keys():
101 if sample not in GFFinstanceDict:
102 GFFinstanceDict[sample]={}
103 subinstance=extractsubinstance(item_upstream_coordinate, item_downstream_coordinate, readDict[sample].instanceDict[chrom])
104 if item_polarity == '-':
105 subinstance.readDict={key*-1:value for key, value in subinstance.readDict.iteritems()}
106 # subinstance.readDict.setdefault(key, [])
107 subinstance.gene=gff_name
108 GFFinstanceDict[sample][gff_name]=subinstance
109 return GFFinstanceDict
110
111 MasterListOfGenomes=process_samples(filePath)
112
113 if args.gff:
114 MasterListOfGenomes=gff_item_subinstances(MasterListOfGenomes, args.gff)
115
116 if global_size:
117 write_size_distribution_dataframe_global(MasterListOfGenomes, size_distribution_file, pol)
118 else:
119 write_size_distribution_dataframe(MasterListOfGenomes, size_distribution_file, pol)