Mercurial > repos > galaxytrakr > hfp_centriflaken_awsbatch

comparison 0.4.2/bin/process_centrifuge_output.py @ 0:082e0091e813 draft default tip

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planemo upload
author galaxytrakr
date Fri, 29 May 2026 13:27:47 +0000
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-1:000000000000 0:082e0091e813
1 #!/usr/bin/env python
2
3 import os
4 import argparse
5 import logging as log
6 import pandas as pd
7 import numpy as np
8 from Bio import SeqIO
9
10
11 def main():
12 # READ IN ARGUMENTS
13 desc = """
14 This script is part of the centriflaken pipeline: It processes centrifuge
15 output and produces either a filtered FASTQ or a text file of FASTQ IDs based
16 on the supplied taxa/bug
17 """
18 parser = argparse.ArgumentParser(prog='process_centrifuge_output.py', description=desc)
19 parser.add_argument("-v", dest='verbose', action="store_true", help="For more verbose output")
20 parser.add_argument("-i", dest='input_fastq', required=False,
21 help="Path to input FASTQ file (same as input to centrifuge). If not mentioned, \
22 a text file of sequence IDs are produced instead of a FASTQ file")
23 parser.add_argument("-t", dest='taxa_filtered_fastq_file', required=True,
24 help="Path to output FASTQ or output text file filtered by the taxa specified")
25 parser.add_argument("-r", dest='cent_report', required=True, help="Path to centrifuge report")
26 parser.add_argument("-o", dest='cent_output', required=True, help="Path to centrifuge output")
27 parser.add_argument("-b", dest='bug', required=True,
28 help="Name or fragment of name of the bug by which reads are extracted")
29 args = parser.parse_args()
30
31 # MORE INFO IF VERBOSE
32 if args.verbose:
33 log.basicConfig(format="%(levelname)s: %(message)s", level=log.DEBUG)
34 else:
35 log.basicConfig(format="%(levelname)s: %(message)s")
36
37 # ASSIGN VARIABLES
38 input_fastq = args.input_fastq
39 taxa_filtered_fastq_file = args.taxa_filtered_fastq_file
40 cent_report = args.cent_report
41 cent_output = args.cent_output
42 bug = args.bug
43 report_col_list = ["name", "taxID"]
44 output_col_list = ["taxID", "readID"]
45
46 # Match and filter taxa names and ids from centrifuge report file
47 report_df = pd.read_csv(cent_report, delimiter="\t", usecols=report_col_list)
48 report_df['name'] = report_df['name'].str.lower()
49 filt_report_df = report_df[report_df['name'].str.contains(bug.lower())]
50 #print("\nMatching taxa names and ids:\n",filt_report_df)
51 taxID_list = filt_report_df['taxID']
52
53 # Match the above tax ids to read ids from centrifuge output file and deduplicate
54 output_df = pd.read_csv(cent_output, delimiter="\t", usecols=output_col_list)
55 filt_output_df = output_df.loc[output_df['taxID'].isin(taxID_list)]
56 readID_list = filt_output_df['readID']
57 readID_dedup_list = np.unique(readID_list)
58 TF=open(taxa_filtered_fastq_file, "w")
59
60 if (not input_fastq):
61 # print("\nFILTERED READ ID LIST:\n", readID_dedup_list)
62 for ID in readID_dedup_list:
63 TF.write(f"{ID}\n")
64 else:
65 # Extract filtered reads from input fastq and write to output fastq
66 print ("Indexing reads..")
67 rec = SeqIO.index(input_fastq,"fastq")
68 for i in readID_dedup_list:
69 if i in rec:
70 SeqIO.write(rec[i], TF, "fastq")
71
72 TF.close()
73
74 if __name__ == "__main__":
75 main()