comparison BlastParser_and_hits.py @ 1:1964514aabde draft

planemo upload for repository https://bitbucket.org/drosofff/gedtools/ commit 1cc2b50091f512593c502176619998f5908fc8e8

0:69ea2a13947f

    the_parser.add_argument('--sequences', action="store", type=str, help="Path to the fasta file with blasted sequences")
    the_parser.add_argument('--fastaOutput', action="store", type=str, help="fasta output file of blast hits")
    the_parser.add_argument('--tabularOutput', action="store", type=str, help="tabular output file of blast analysis")
    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")
    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')
    if not args.flanking:
        args.flanking = 0

        leftCoordinate -= FlankingValue
    else:
        leftCoordinate = 1
    return getseq (fastadict, FastaHeader, leftCoordinate, rightCoordinate, polarity)
    
def outputParsing (F, Fasta, results, Xblastdict, fastadict, mode="verbose"):
    F= open(F, "w")
    Fasta=open(Fasta, "w")
    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, "# Maximum 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\tMaximum 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"])

                print >> Fasta, ">%s\n%s" % (header, insert_newlines(results[subject]["HitDic"][header]) )
            print >> Fasta, "" # final carriage return for the sequence
    F.close()
    Fasta.close()
        
    

def __main__ ():
    args = Parser()
    fastadict = getfasta (args.sequences)
    Xblastdict = getblast (args.blast)
    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)
    outputParsing (args.tabularOutput, args.fastaOutput, results, Xblastdict, fastadict, args.mode)
if __name__=="__main__": __main__()

1:1964514aabde

    the_parser.add_argument('--sequences', action="store", type=str, help="Path to the fasta file with blasted sequences")
    the_parser.add_argument('--fastaOutput', action="store", type=str, help="fasta output file of blast hits")
    the_parser.add_argument('--tabularOutput', action="store", type=str, help="tabular output file of blast analysis")
    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 maximum BitScore below the specified float number")
    the_parser.add_argument('--filter_meanScore', action="store", type=float, default=0, help="filter out maximum BitScore 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')
    if not args.flanking:
        args.flanking = 0

        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")
    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, "# Maximum 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\tMaximum 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"])

                print >> Fasta, ">%s\n%s" % (header, insert_newlines(results[subject]["HitDic"][header]) )
            print >> Fasta, "" # final carriage return for the sequence
    F.close()
    Fasta.close()
        
def sort_sequences (fastadict, blastdict, matched_sequences, unmatched_sequences):
    '''to output the sequences that matched and did not matched in the blast'''
    blasted_transcripts = []
    for subject in blastdict:
        for transcript in blastdict[subject]:
            blasted_transcripts.append(transcript)
    blasted_transcripts = list( set( blasted_transcripts))
    F_matched = open (matched_sequences, "w")
    F_unmatched = open (unmatched_sequences, "w")
    for transcript in fastadict:
        if transcript in blasted_transcripts:
            print >> F_matched, ">%s\n%s" % (transcript, insert_newlines(fastadict[transcript]) )
        else:
            print >> F_unmatched, ">%s\n%s" % (transcript, insert_newlines(fastadict[transcript]) )
    F_matched.close()
    F_unmatched.close()
    return

def __main__ ():
    args = Parser()
    fastadict = getfasta (args.sequences)
    Xblastdict = getblast (args.blast)
    sort_sequences (fastadict, Xblastdict, args.al_sequences, args.un_sequences)
    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)
    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)
if __name__=="__main__": __main__()