diff cmpb2016/ext_repertoire_V.py @ 0:8be019b173e6 draft

Uploaded included tools

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/cmpb2016/ext_repertoire_V.py	Sun Mar 18 05:54:20 2018 -0400
@@ -0,0 +1,69 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Jun 20 14:58:08 2014
+
+@author: chmaramis
+"""
+
+from __future__ import division
+import numpy as np
+from pandas import *
+import functools as ft
+import sys
+import time
+
+frm = lambda x,y: '{r}/{l}'.format(r=x,l=y) 
+
+def repertoireComputation(inp_name, fname):
+        
+    df = DataFrame()
+    df = read_csv(inp_name, sep='\t', index_col=0 )
+    #tp = read_csv(inp_name, iterator=True, chunksize=5000,sep='\t', index_col=0 )
+    #df = concat([chunk for chunk in tp])     
+    
+    
+    vgroup = df.groupby(['V-GENE'])
+    vdi = vgroup.size()
+    rep = DataFrame(list(vdi.index), columns=['V-GENE'])
+    rep['Reads'] = vdi.values 
+    #rep['Reads/Total'] = ['{r}/{l}'.format(r=p , l = len(df)) for p in vdi.values]
+    rep['Reads/Total'] = rep['Reads'].map(ft.partial(frm, y=len(df)))
+    rep['Frequency %'] = (100*rep['Reads']/len(df)).map('{:.4f}'.format)
+    
+    rep = rep.sort_values(by = ['Reads'] , ascending = False)
+    rep.index = range(1,len(rep)+1)
+
+    su = rep[['V-GENE','Frequency %']].head(10)
+    spl = fname.split('_')
+    summdf = DataFrame([su['V-GENE'].values[0],su['Frequency %'].values[0]],
+                       index = ['Dominant V-GENE','Frequency'], columns = [spl[0]])
+    summdf['%'] = ''
+
+    return (rep, su, summdf)
+
+
+if __name__ == '__main__':   
+
+    start=time.time()
+
+    # Parse input arguments    
+    inp_name = sys.argv[1]
+    outrep = sys.argv[2]
+    summ_rep = sys.argv[3]
+    summ_rep2 = sys.argv[4]
+    fname = sys.argv[5]
+            
+    # Execute basic function
+    rep, su, summdf = repertoireComputation(inp_name, fname)
+    
+    # Save output to CSV files
+    if not rep.empty: 
+        rep.to_csv(outrep, sep = '\t')
+    if not su.empty:
+        su.to_csv(summ_rep, sep = '\t')
+    if not summdf.empty:
+        summdf.to_csv(summ_rep2, sep = '\t')
+        
+    # Print execution time
+    stop=time.time()
+    print('Runtime:' + str(stop-start))