--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/signature.py	Mon Nov 03 10:29:28 2014 -0500
@@ -0,0 +1,91 @@
+#!/usr/bin/python
+# script for computing overlap signatures from a bowtie output
+# Christophe Antoniewski <drosofff@gmail.com>
+# Usage signature.py <1:input> <2:format of input> <3:minsize query> <4:maxsize query> <5:minsize target> <6:maxsize target>
+#			  <7:minscope> <8:maxscope> <9:output> <10:bowtie index> <11:procedure option> <12: graph (global or lattice)>
+# 			  <13: R code>
+# version 2.0.0
+
+import sys, subprocess, argparse
+from smRtools import *
+from collections import defaultdict # test whether it is required
+
+def Parser():
+  the_parser = argparse.ArgumentParser()
+  the_parser.add_argument('--input', action="store", type=str, help="input alignment file")
+  the_parser.add_argument('--inputFormat', action="store", type=str, choices=["tabular", "bam", "sam"], help="format of alignment file (tabular/bam/sam)")
+  the_parser.add_argument('--minquery', type=int, help="Minimum readsize of query reads (nt) - must be an integer")
+  the_parser.add_argument('--maxquery', type=int, help="Maximum readsize of query reads (nt) - must be an integer")
+  the_parser.add_argument('--mintarget', type=int, help="Minimum readsize of target reads (nt) - must be an integer")
+  the_parser.add_argument('--maxtarget', type=int, help="Maximum readsize of target reads (nt) - must be an integer")
+  the_parser.add_argument('--minscope', type=int, help="Minimum overlap analyzed (nt) - must be an integer")
+  the_parser.add_argument('--maxscope', type=int, help="Maximum overlap analyzed (nt) - must be an integer")
+  the_parser.add_argument('--outputOverlapDataframe', action="store", type=str, help="Overlap dataframe")
+  the_parser.add_argument('--referenceGenome', action='store', help="path to the bowtie-indexed or fasta reference")
+  the_parser.add_argument('--extract_index', action='store_true', help="specify if the reference is an indexed Bowtie reference")
+  the_parser.add_argument('--graph', action='store', choices=["global", "lattice"], help="small RNA signature is computed either globally or by item (global-lattice)")
+  the_parser.add_argument('--rcode', type=str, help="R code to be passed to the python script")
+  args = the_parser.parse_args()
+  return args
+
+args = Parser()
+
+if args.extract_index:
+  GenomeFormat = "bowtieIndex"
+else:
+  GenomeFormat = "fastaSource"
+
+if args.inputFormat == "tabular":
+  Genome = HandleSmRNAwindows (args.input, args.inputFormat, args.referenceGenome, GenomeFormat)
+elif args.inputFormat == "sam":
+  Genome = HandleSmRNAwindows (args.input, args.inputFormat, args.referenceGenome, GenomeFormat)
+else:
+  Genome = HandleSmRNAwindows (args.input, args.inputFormat, args.referenceGenome, GenomeFormat)
+
+# replace objDic by Genome.instanceDict or... objDic = Genome.instanceDict
+objDic = Genome.instanceDict
+
+args.maxscope += 1
+
+general_frequency_table = dict ([(i,0) for i in range(args.minscope, args.maxscope)])
+general_percent_table = dict ([(i,0) for i in range(args.minscope, args.maxscope)])
+OUT = open (args.outputOverlapDataframe, "w")
+
+if args.graph == "global":
+  ###### for normalized summing of local_percent_table(s)
+  readcount_dic = {}
+  Total_read_in_objDic = 0
+  for item in objDic:
+    readcount_dic[item] = objDic[item].readcount(args.minquery, args.maxquery)
+    Total_read_in_objDic += readcount_dic[item]
+  ######
+  for x in (objDic):
+    local_frequency_table = objDic[x].signature( args.minquery, args.maxquery, args.mintarget, args.maxtarget, range(args.minscope, args.maxscope) )
+    local_percent_table = objDic[x].hannon_signature( args.minquery, args.maxquery, args.mintarget, args.maxtarget, range(args.minscope, args.maxscope) )
+    try:
+      for overlap in local_frequency_table.keys():
+        general_frequency_table[overlap] = general_frequency_table.get(overlap, 0) + local_frequency_table[overlap]
+    except:
+      pass
+    try:
+      for overlap in local_percent_table.keys():
+        general_percent_table[overlap] = general_percent_table.get(overlap, 0) + (1./Total_read_in_objDic*readcount_dic[x]*local_percent_table[overlap])
+    except:
+      pass
+  print >> OUT, "overlap\tnum of pairs\tprobability"
+  for classe in sorted(general_frequency_table):
+    print >> OUT, "%i\t%i\t%f" % (classe, general_frequency_table[classe], general_percent_table[classe])
+
+else:
+  print >> OUT, "overlap\tnum of pairs\tprobability\titem"
+  for x in (objDic):
+    local_frequency_table = objDic[x].signature( args.minquery, args.maxquery, args.mintarget, args.maxtarget, range(args.minscope, args.maxscope) )
+    local_percent_table = objDic[x].hannon_signature( args.minquery, args.maxquery, args.mintarget, args.maxtarget, range(args.minscope, args.maxscope) )
+    for classe in range(args.minscope, args.maxscope):
+      print >> OUT, "%i\t%i\t%f\t%s" % (classe, local_frequency_table[classe], local_percent_table[classe], x)
+
+OUT.close()
+
+## Run the R script that is defined in the xml using the Rscript binary provided with R.
+R_command="Rscript "+ args.rcode
+process = subprocess.Popen(R_command.split())