comparison BlastParser_and_hits.py @ 4:60b6bd959929 draft

planemo upload for repository https://github.com/ARTbio/tools-artbio/tree/master/tools/msp_blastparser_and_hits commit e842488e979d8a00b9646061573355cb427bc89c

3:8f5d48294f70

#!/usr/bin/python
#  blastn blastx parser revised debugged: 3-4-2015. Commit issue.
# [e-mail]

import sys
import argparse
from collections import defaultdict

    the_parser.add_argument('--flanking', action="store", type=int, help="number of flanking nucleotides added to the hit sequences") 
    the_parser.add_argument('--mode', action="store", choices=["verbose", "short"], type=str, help="reporting (verbose) or not reporting (short) oases contigs")
    the_parser.add_argument('--filter_relativeCov', action="store", type=float, default=0, help="filter out relative coverages below the specified ratio (float number)")
    the_parser.add_argument('--filter_maxScore', action="store", type=float, default=0, help="filter out best BitScores below the specified float number")
    the_parser.add_argument('--filter_meanScore', action="store", type=float, default=0, help="filter out mean BitScores below the specified float number")
    the_parser.add_argument('--al_sequences', action="store", type=str, help="sequences that have been blast aligned")
    the_parser.add_argument('--un_sequences', action="store", type=str, help="sequences that have not been blast aligned")
    args = the_parser.parse_args()
    if not all ( (args.sequences, args.blast, args.fastaOutput, args.tabularOutput) ):
        the_parser.error('argument(s) missing, call the -h option of the script')

        leftCoordinate -= FlankingValue
    else:
        leftCoordinate = 1
    return getseq (fastadict, FastaHeader, leftCoordinate, rightCoordinate, polarity)
    
def outputParsing (F, Fasta, results, Xblastdict, fastadict, filter_relativeCov=0, filter_maxScore=0, filter_meanScore=0, mode="verbose"):
    F= open(F, "w")
    Fasta=open(Fasta, "w")
    blasted_transcripts = []
    for subject in results:
        if results[subject]["RelativeSubjectCoverage"]<filter_relativeCov or results[subject]["maxBitScores"]<filter_maxScore or results[subject]["meanBitScores"]<filter_meanScore:
            continue
        for transcript in Xblastdict[subject]:
            blasted_transcripts.append(transcript)
    blasted_transcripts = list( set( blasted_transcripts))
    if mode == "verbose":
        print >>F, "# SeqId\t%Identity\tAlignLength\tStartSubject\tEndSubject\t%QueryHitCov\tE-value\tBitScore\n"
        for subject in sorted (results, key=lambda x: results[x]["meanBitScores"], reverse=True):
            if results[subject]["RelativeSubjectCoverage"]<filter_relativeCov or results[subject]["maxBitScores"]<filter_maxScore or results[subject]["meanBitScores"]<filter_meanScore:
                continue
            print >> F, "#\n# %s" % subject
            print >> F, "# Suject Length: %s" % (results[subject]["subjectLength"])
            print >> F, "# Total Subject Coverage: %s" % (results[subject]["TotalCoverage"])
            print >> F, "# Relative Subject Coverage: %s" % (results[subject]["RelativeSubjectCoverage"])
            print >> F, "# Best Bit Score: %s" % (results[subject]["maxBitScores"])

                    info = "\t".join(info)
                    print >> F, info
    else:
        print >>F, "# subject\tsubject length\tTotal Subject Coverage\tRelative Subject Coverage\tBest Bit Score\tMean Bit Score"
        for subject in sorted (results, key=lambda x: results[x]["meanBitScores"], reverse=True):
            if results[subject]["RelativeSubjectCoverage"]<filter_relativeCov or results[subject]["maxBitScores"]<filter_maxScore or results[subject]["meanBitScores"]<filter_meanScore:
                continue
            line = []
            line.append(subject)
            line.append(results[subject]["subjectLength"])
            line.append(results[subject]["TotalCoverage"])
            line.append(results[subject]["RelativeSubjectCoverage"])

    results = defaultdict(dict)
    for subject in Xblastdict:
        results[subject]["HitDic"], results[subject]["subjectLength"], results[subject]["TotalCoverage"], results[subject]["RelativeSubjectCoverage"], results[subject]["maxBitScores"], results[subject]["meanBitScores"]  = subjectCoverage(fastadict, Xblastdict, subject, args.flanking)
    blasted_transcripts = outputParsing (args.tabularOutput, args.fastaOutput, results, Xblastdict, fastadict,
                                        filter_relativeCov=args.filter_relativeCov, filter_maxScore=args.filter_maxScore,
                                        filter_meanScore=args.filter_meanScore, mode=args.mode)
    dispatch_sequences (fastadict, blasted_transcripts, args.al_sequences, args.un_sequences)

if __name__=="__main__": __main__()

4:60b6bd959929

#!/usr/bin/python
#  blastn tblastn blastx parser revised 14-1-2016.
# [e-mail]

import sys
import argparse
from collections import defaultdict

    the_parser.add_argument('--flanking', action="store", type=int, help="number of flanking nucleotides added to the hit sequences") 
    the_parser.add_argument('--mode', action="store", choices=["verbose", "short"], type=str, help="reporting (verbose) or not reporting (short) oases contigs")
    the_parser.add_argument('--filter_relativeCov', action="store", type=float, default=0, help="filter out relative coverages below the specified ratio (float number)")
    the_parser.add_argument('--filter_maxScore', action="store", type=float, default=0, help="filter out best BitScores below the specified float number")
    the_parser.add_argument('--filter_meanScore', action="store", type=float, default=0, help="filter out mean BitScores below the specified float number")
    the_parser.add_argument('--filter_term_in', action="store", type=str, default="", help="select the specified term in the subject list")
    the_parser.add_argument('--filter_term_out', action="store", type=str, default="", help="exclude the specified term from the subject list")
    the_parser.add_argument('--al_sequences', action="store", type=str, help="sequences that have been blast aligned")
    the_parser.add_argument('--un_sequences', action="store", type=str, help="sequences that have not been blast aligned")
    args = the_parser.parse_args()
    if not all ( (args.sequences, args.blast, args.fastaOutput, args.tabularOutput) ):
        the_parser.error('argument(s) missing, call the -h option of the script')

        leftCoordinate -= FlankingValue
    else:
        leftCoordinate = 1
    return getseq (fastadict, FastaHeader, leftCoordinate, rightCoordinate, polarity)
    
def outputParsing (F, Fasta, results, Xblastdict, fastadict, filter_relativeCov=0, filter_maxScore=0, filter_meanScore=0, filter_term_in="", filter_term_out="", mode="verbose"):
    def filter_results (results, filter_relativeCov=0, filter_maxScore=0, filter_meanScore=0, filter_term_in="", filter_term_out=""):
        print "###", filter_term_in
        for subject in results.keys():
            if results[subject]["RelativeSubjectCoverage"]<filter_relativeCov:
                del results[subject]
                continue
            if results[subject]["maxBitScores"]<filter_maxScore:
                del results[subject]
                continue
            if results[subject]["meanBitScores"]<filter_meanScore:
                del results[subject]
                continue
            if filter_term_in in subject:
                pass
            else:
                del results[subject]
                continue
            if filter_term_out and filter_term_out in subject:
                del results[subject]
                continue
        return results
        
    F= open(F, "w")
    Fasta=open(Fasta, "w")
    blasted_transcripts = []
    filter_results (results, filter_relativeCov, filter_maxScore, filter_meanScore, filter_term_in, filter_term_out)
    for subject in results:
        for transcript in Xblastdict[subject]:
            blasted_transcripts.append(transcript)
    blasted_transcripts = list( set( blasted_transcripts))
    if mode == "verbose":
        print >>F, "# SeqId\t%Identity\tAlignLength\tStartSubject\tEndSubject\t%QueryHitCov\tE-value\tBitScore\n"
        for subject in sorted (results, key=lambda x: results[x]["meanBitScores"], reverse=True):
            print >> F, "#\n# %s" % subject
            print >> F, "# Suject Length: %s" % (results[subject]["subjectLength"])
            print >> F, "# Total Subject Coverage: %s" % (results[subject]["TotalCoverage"])
            print >> F, "# Relative Subject Coverage: %s" % (results[subject]["RelativeSubjectCoverage"])
            print >> F, "# Best Bit Score: %s" % (results[subject]["maxBitScores"])

                    info = "\t".join(info)
                    print >> F, info
    else:
        print >>F, "# subject\tsubject length\tTotal Subject Coverage\tRelative Subject Coverage\tBest Bit Score\tMean Bit Score"
        for subject in sorted (results, key=lambda x: results[x]["meanBitScores"], reverse=True):
            line = []
            line.append(subject)
            line.append(results[subject]["subjectLength"])
            line.append(results[subject]["TotalCoverage"])
            line.append(results[subject]["RelativeSubjectCoverage"])

    results = defaultdict(dict)
    for subject in Xblastdict:
        results[subject]["HitDic"], results[subject]["subjectLength"], results[subject]["TotalCoverage"], results[subject]["RelativeSubjectCoverage"], results[subject]["maxBitScores"], results[subject]["meanBitScores"]  = subjectCoverage(fastadict, Xblastdict, subject, args.flanking)
    blasted_transcripts = outputParsing (args.tabularOutput, args.fastaOutput, results, Xblastdict, fastadict,
                                        filter_relativeCov=args.filter_relativeCov, filter_maxScore=args.filter_maxScore,
                                        filter_meanScore=args.filter_meanScore, filter_term_in=args.filter_term_in,
                                        filter_term_out=args.filter_term_out, mode=args.mode)
    dispatch_sequences (fastadict, blasted_transcripts, args.al_sequences, args.un_sequences)

if __name__=="__main__": __main__()