--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/size_histogram.py	Tue Jul 11 11:44:36 2017 -0400
@@ -0,0 +1,119 @@
+#!/usr/bin/python
+# python parser module for size distributions, guided by GFF3
+
+import argparse
+import subprocess
+from collections import OrderedDict
+from smRtools import extractsubinstance
+from smRtools import HandleSmRNAwindows
+
+
+def Parser():
+  the_parser = argparse.ArgumentParser()
+  the_parser.add_argument('--output_size_distribution', action="store", type=str, help="size distribution dataframe")
+  the_parser.add_argument('--reference_fasta', action="store", type=str, help="output file")
+  the_parser.add_argument('--reference_bowtie_index',action='store', help="paths to indexed or fasta references")
+  the_parser.add_argument('--input',nargs='+', help="paths to multiple input files")
+  the_parser.add_argument('--ext',nargs='+', help="input file type")
+  the_parser.add_argument('--label',nargs='+', help="labels of multiple input files")
+  the_parser.add_argument('--normalization_factor',nargs='+', type=float, help="Normalization factor for input file")
+  the_parser.add_argument('--gff', type=str, help="GFF containing regions of interest")
+  the_parser.add_argument('--minquery', type=int, help="Minimum readsize")
+  the_parser.add_argument('--maxquery', type=int, help="Maximum readsize")
+  the_parser.add_argument('--global_size', action="store_true", help="if specified, size distribution is calculated for the sum of all items")
+  the_parser.add_argument('--collapse', action="store_true", help="if specified, forward and reverse reads are collapsed")
+  args = the_parser.parse_args()
+  return args
+
+
+args=Parser()
+if args.reference_fasta:
+  genomeRefFormat = "fastaSource"
+  genomeRefFile = args.reference_fasta  
+if args.reference_bowtie_index:
+  genomeRefFormat = "bowtieIndex"
+  genomeRefFile = args.reference_bowtie_index  
+size_distribution_file=args.output_size_distribution
+minquery=args.minquery
+maxquery=args.maxquery
+filePath=args.input
+fileExt=args.ext
+fileLabel=args.label
+normalization_factor=args.normalization_factor
+global_size=args.global_size
+collapse=args.collapse
+
+if collapse:
+  pol=["both"]
+else:
+  pol=["F", "R"]
+
+MasterListOfGenomes = OrderedDict()
+
+def process_samples(filePath):
+  for i, filePath in enumerate(filePath):
+    norm=normalization_factor[i]
+    print fileLabel[i]
+    MasterListOfGenomes[fileLabel[i]] = HandleSmRNAwindows (alignmentFile=filePath, alignmentFileFormat=fileExt[i], genomeRefFile=genomeRefFile, genomeRefFormat=genomeRefFormat,\
+                        biosample=fileLabel[i], size_inf=minquery, size_sup=maxquery, norm=norm)
+  return MasterListOfGenomes
+
+
+def write_size_distribution_dataframe(readDict, size_distribution_file, pol=["both"] ):
+  '''refactored on 7-9-2014'''
+  with open(size_distribution_file, 'w') as size_distrib:
+    print >>size_distrib, "gene\tpolarity\tsize\tcount\tsample"
+    for sample in readDict.keys():
+      if args.gff:
+        dict=readDict[sample]
+      else:
+        dict=readDict[sample].instanceDict
+      for gene in dict.keys():
+        histogram = dict[gene].size_histogram()
+        for polarity in pol:
+          for size, count in histogram[polarity].iteritems():
+            print >>size_distrib, "%s\t%s\t%s\t%s\t%s" % (gene, polarity, size, count, sample)
+
+
+def write_size_distribution_dataframe_global(readDict, size_distribution_file, pol=["both"]):
+  with open(size_distribution_file, 'w') as size_distrib:
+    print >>size_distrib, "gene\tpolarity\tsize\tcount\tsample"
+    for sample in readDict.keys():
+      histogram = readDict[sample].size_histogram()
+      gene="sample"
+      for polarity in pol:
+        for size, count in histogram[polarity].iteritems():
+          print >>size_distrib, "%s\t%s\t%s\t%s\t%s" % (gene, polarity, size, count, sample)
+
+
+def gff_item_subinstances(readDict, gff3):
+  GFFinstanceDict=OrderedDict()
+  with open(gff3) as gff:
+    for line in gff:
+      if line[0] == "#": continue
+      gff_fields = line[:-1].split("\t")
+      chrom = gff_fields[0]
+      gff_name = gff_fields[-1].split("Name=")[-1].split(";")[0] # to isolate the GFF Name
+      item_upstream_coordinate = int(gff_fields[3])
+      item_downstream_coordinate = int(gff_fields[4])
+      item_polarity = gff_fields[6]
+      for sample in readDict.keys():
+        if sample not in GFFinstanceDict:
+          GFFinstanceDict[sample]={}
+        subinstance=extractsubinstance(item_upstream_coordinate, item_downstream_coordinate, readDict[sample].instanceDict[chrom])
+        if item_polarity == '-':
+          subinstance.readDict={key*-1:value for key, value in subinstance.readDict.iteritems()}
+#          subinstance.readDict.setdefault(key, [])
+        subinstance.gene=gff_name
+        GFFinstanceDict[sample][gff_name]=subinstance
+  return GFFinstanceDict
+
+MasterListOfGenomes=process_samples(filePath)
+
+if args.gff:
+  MasterListOfGenomes=gff_item_subinstances(MasterListOfGenomes, args.gff)
+
+if global_size:
+  write_size_distribution_dataframe_global(MasterListOfGenomes, size_distribution_file, pol)
+else:
+  write_size_distribution_dataframe(MasterListOfGenomes, size_distribution_file, pol)
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