# HG changeset patch
# User tyty
# Date 1413783810 14400
# Node ID 13cf6f40ad1e1d669a597416b47a70e4dd12adb6
# Parent  b0243634fe6b27c03a175326f3ecc0847712e039
Uploaded

diff -r b0243634fe6b -r 13cf6f40ad1e reactivity_cal/react_cal.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/reactivity_cal/react_cal.py	Mon Oct 20 01:43:30 2014 -0400
@@ -0,0 +1,136 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+import sys
+from Bio import SeqIO
+import math
+from parse_dis_react import *
+from react_norm_function import *
+import os
+
+
+dist_file1 = sys.argv[1] #plus library
+dist_file2 = sys.argv[2] #minus library
+seq_file = sys.argv[3] #Reference library(genome/cDNA)
+nt_spec = sys.argv[4] #only show reactivity for AC or ATCG
+flag_in = sys.argv[5] # perform 2-8% normalization (1) or not (0)
+threshold = sys.argv[6] #Threshold to cap the reactivities
+output_file = sys.argv[7]
+
+
+distri_p = parse_dist(dist_file1)
+distri_m = parse_dist(dist_file2)
+threshold = float(threshold)
+
+
+ospath = os.path.realpath(sys.argv[0])
+ost = ospath.split('/')
+syspath = ""
+for i in range(len(ost)-1):
+    syspath = syspath+ost[i].strip()
+    syspath = syspath+'/' 
+
+h = file(syspath+"react.txt",'w')
+flag_in = int(flag_in)
+
+seqs = SeqIO.parse(open(seq_file),'fasta');
+nt_s = set()
+for i in range(len(nt_spec)):
+    nt_s.add(nt_spec[i])
+
+flag = 0
+trans = []
+distri_p = distri_p[1]
+distri_m = distri_m[1]
+
+#thres = int(threshold)
+
+
+transcripts = {}
+for seq in seqs:
+    n = seq.id
+    trans.append(n)
+    transcripts[n] = seq.seq.tostring()
+    
+
+#print(distri_p)
+        
+
+for i in range(0, len(trans)):
+    h.write(trans[i])
+    h.write('\n')       
+    for j in range(len(distri_p[trans[i]])):
+        distri_p[trans[i]][j] = math.log((int(distri_p[trans[i]][j])+1),math.e)
+    for j in range(len(distri_m[trans[i]])):
+        distri_m[trans[i]][j] = math.log((int(distri_m[trans[i]][j])+1),math.e)       
+    s_p = sum(distri_p[trans[i]])
+    s_m = sum(distri_m[trans[i]])
+    length = len(distri_p[trans[i]])
+    if s_p!= 0 and s_m!= 0:
+        r = []
+        for j in range(0, len(distri_p[trans[i]])):
+            f_p = (float(distri_p[trans[i]][j]))/float(s_p)*length
+            f_m = (float(distri_m[trans[i]][j]))/float(s_m)*length
+            raw_react = f_p-f_m
+            r.append(max(0, raw_react))
+                
+    if s_p!= 0 and s_m!= 0:    
+        for k in range(1,(len(r)-1)):
+            if transcripts[trans[i]][k-1] in nt_s:
+                h.write(str(r[k]))
+                h.write('\t')
+            else:
+                h.write('NA')
+                h.write('\t')
+        k = k+1
+        if transcripts[trans[i]][k-1] in nt_s:
+            h.write(str(r[k]))
+            h.write('\n')
+        else:
+            h.write('NA')
+            h.write('\n')
+            
+
+h.close()
+
+if flag_in:
+    react_norm((syspath+"react.txt"),output_file, threshold)
+else:
+    h_o = file(output_file, 'w')
+    f_i = open(syspath+"react.txt")
+    for aline in f_i.readlines():
+        h_o.write(aline.strip())
+        h_o.write('\n')
+os.system("rm -f "+syspath+"react.txt")
+    
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