# HG changeset patch
# User yboursin
# Date 1476967626 14400
# Node ID 340ada00d965e76a2ebfc4195edc2e446e27a2ce
# Parent  00231125f4fb401d56161ca8ddbfd031c64fad21
Uploaded

diff -r 00231125f4fb -r 340ada00d965 pre_EBSeq.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/pre_EBSeq.py	Thu Oct 20 08:47:06 2016 -0400
@@ -0,0 +1,54 @@
+#!/usr/bin/env python
+# Author: rachel.legendre@pasteur.fr
+
+from os.path import basename, join
+from os import getcwd, system
+import argparse
+from shutil import copyfile
+import tempfile
+import csv
+import pandas as pd
+from collections import Counter
+
+def __main__():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--inputs', action='append', nargs='*')
+    parser.add_argument('--outvector')
+    parser.add_argument('--outtable')
+    args = parser.parse_args()
+
+    IGvector = args.outvector
+    outtable = args.outtable
+    inputs = args.inputs
+    working_directory = getcwd()
+
+    dfs = []
+
+    #Build the Expression table from the "expected_count" column of RSEM count table
+    for (filename, cond) in inputs:
+        # read the csv, making sure the first two columns are str
+        df = pd.read_csv(filename,  sep='\t', converters={0: str, 1: str})
+        # throw away all but the first two columns
+        df = df.iloc[:, [0,1,4]]
+        # change the column names so they won't collide during concatenation
+        df = df.rename(index=str, columns={"expected_count": cond})
+        dfs.append(df)
+    # concatenate them horizontally
+    df_final = reduce(lambda left, right: pd.merge(left, right, on=['gene_id','transcript_id(s)']), dfs)
+    # write it out
+    df_final.to_csv(outtable, index=None, sep="\t")
+
+
+    #get IG vector from the Expression Table
+    #The IG Vector is a table with only one column of numbers (integers)
+    df2 = pd.read_csv(outtable,  sep='\t', converters={0: str, 1: str})
+    ids= df2[['transcript_id(s)', 'gene_id']]
+    counts = Counter(ids['gene_id'])
+    gene_order = list(ids['gene_id'])
+    with open(IGvector, 'wb') as IG:
+        for gene in gene_order:
+            nbG = counts[gene]
+            IG.write(str(nbG) + '\n')
+
+if __name__ == "__main__":
+    __main__()