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1 #!/usr/bin/env python
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2 # Author: rachel.legendre@pasteur.fr
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3
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4 from os.path import basename, join
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5 from os import getcwd, system
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6 import argparse
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7 from shutil import copyfile
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8 import tempfile
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9 import csv
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10 import pandas as pd
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11 from collections import Counter
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12
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13 def __main__():
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14 parser = argparse.ArgumentParser()
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15 parser.add_argument('--inputs', action='append', nargs='*')
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16 parser.add_argument('--outvector')
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17 parser.add_argument('--outtable')
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18 args = parser.parse_args()
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19
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20 IGvector = args.outvector
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21 outtable = args.outtable
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22 inputs = args.inputs
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23 working_directory = getcwd()
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24
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25 dfs = []
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26
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27 #Build the Expression table from the "expected_count" column of RSEM count table
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28 for (filename, cond) in inputs:
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29 # read the csv, making sure the first two columns are str
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30 df = pd.read_csv(filename, sep='\t', converters={0: str, 1: str})
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31 # throw away all but the first two columns
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32 df = df.iloc[:, [0,1,4]]
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33 # change the column names so they won't collide during concatenation
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34 df = df.rename(index=str, columns={"expected_count": cond})
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35 dfs.append(df)
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36 # concatenate them horizontally
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37 df_final = reduce(lambda left, right: pd.merge(left, right, on=['gene_id','transcript_id(s)']), dfs)
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38 # write it out
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39 df_final.to_csv(outtable, index=None, sep="\t")
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40
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41
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42 #get IG vector from the Expression Table
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43 #The IG Vector is a table with only one column of numbers (integers)
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44 df2 = pd.read_csv(outtable, sep='\t', converters={0: str, 1: str})
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45 ids= df2[['transcript_id(s)', 'gene_id']]
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46 counts = Counter(ids['gene_id'])
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47 gene_order = list(ids['gene_id'])
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48 with open(IGvector, 'wb') as IG:
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49 for gene in gene_order:
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50 nbG = counts[gene]
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51 IG.write(str(nbG) + '\n')
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52
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53 if __name__ == "__main__":
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54 __main__()
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