Generating K-mer Count-Based Features with mlgenofeatures Snakemake Workflow

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Generating simulated and actual k-mer count-based features with mlgenofeatures

The mlgenofeatures Snakemake workflow can be used to create files of k-mer counts from actual or simulated short read datasets from a diverse set of mutated haplotype reference sequences.

These k-mer counts can then be used as input to scripts in the mlgenotype python package to train random forest classifiers to recognize large structural variants in real whole genome datasets.

Software dependencies

The mlgenofeatures pipeline requires:

  • Snakemake (https://snakemake.readthedocs.io/en/stable/)

  • ART version ART-MountRainer-2016-06-05 (https://www.niehs.nih.gov/research/resources/software/biostatistics/art/index.cfm)

  • meryl version 1.3 (https://github.com/marbl/meryl)

  • Python with the pysam library (https://pysam.readthedocs.io/en/latest/)

Code Snippets

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import os
import re
import gzip
from collections import namedtuple

def retrieve_genotype(match):
    genolist = []
    genolist.append(match.group(2))
    genolist.append(match.group(4))

    return genolist

with open(snakemake.log[0], "w") as f:
    sys.stderr = sys.stdout = f

    # kmer count file has kmer counts from the simulated fastq file
    kmer_count_file = snakemake.input[0]

    # all kmer file establishes the order of the columns, so all sequence sets will generate the same columns in their feature files
    all_kmer_file = snakemake.input[1]

    # feature file will contain a column for each kmer with counts
    feature_file = snakemake.output[0]

    match = re.search(r'^features/(\S{2})\_(\S{4})\_(\S{2})\_(\S{4})\.(\d+)x\.(\d+)\.features.txt$', feature_file)

    if match:
        genotypelist = retrieve_genotype(match)
        genotypestring = "_".join(genotypelist)

        print("Found genotype " + genotypestring)

        kmercounts = {}

        print("Opening " + kmer_count_file)
        with open(kmer_count_file, "r") as inkmercount_f:
            for line in inkmercount_f:
                line = line.strip()
                countmatch = re.search(r'^(\S+)\s(\d+)$', line)
                if countmatch:
                    currentkmer = countmatch.group(1)
                    currentcount = countmatch.group(2)
                    kmercounts[currentkmer] = currentcount
                    #print("Recording kmer " + currentkmer + " with count " + currentcount)
                else:
                    print("Can\'t find kmer in line:\n" + line)

        print("Successfully read in simulated kmer counts from file " + kmer_count_file)

        # calculate total counts for this sample:
        # append normalized kmer counts to a list for printing:
        kmertotal = 0
        numkmers = 0
        countlist = [] 
        with open(all_kmer_file, "r") as inallkmers_f:
            for line in inallkmers_f:
                line = line.strip()
                kmermatch = re.search(r'^(\S+)\s(\d+)$', line)
                if kmermatch:
                    numkmers = numkmers + 1
                    printkmer = kmermatch.group(1)
                    if kmercounts.get(printkmer) == None:
                        countlist.append("0")
                    else:
                        countlist.append(str(kmercounts[printkmer]))
                        kmertotal = kmertotal + int(kmercounts[printkmer])
                else:
                    print("Can\'t find kmer in line:\n" + line)

        print("Normalizing")
        normcountlist = []
        for count in countlist:
            normcountlist.append(str(round(50.0*int(count)*numkmers/kmertotal)))
        normcountlist.append(genotypestring)

        with open(feature_file, "w") as outfeature_f:
            featurestring = "\t".join(normcountlist)
            print(featurestring, file=outfeature_f)
    else:
        print("Couldn\'t parse filename " + feature_file)
Python From line 1 of scripts/create_featurefile.py 
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import os
import re
import gzip
import pysam
from collections import namedtuple

def print60(seq, outfh):
    for i in range(0, len(seq), 60):
        if i+60 <= len(seq):
            print(seq[i:i+60], file=outfh)
        else:
            print(seq[i:len(seq)], file=outfh)

def gatherdata(match):
    Samplegenodata = namedtuple("Samplegenodata", ["samples", "genotypes", "genomefiles", "mutationfiles"])

    samplelist = []
    genolist = []
    genofilelist = []
    mutfilelist = []
    samplelist.append(match.group(1))
    samplelist.append(match.group(3))
    genolist.append(match.group(2))
    genolist.append(match.group(4))
    genofilelist.append(snakemake.config["genomefiles"][samplelist[0]])
    genofilelist.append(snakemake.config["genomefiles"][samplelist[1]])
    mutfilelist.append(snakemake.config["mutationfiles"][samplelist[0]])
    mutfilelist.append(snakemake.config["mutationfiles"][samplelist[1]])

    return Samplegenodata(samplelist, genolist, genofilelist, mutfilelist)

def retrievemutdata(mutfile, geno):
    Mutationdata = namedtuple("Mutationdata", ["mutation", "mutentry", "mutstart", "mutend", "regionoffset", "regionstart", "regionend", "regionstrand"])

    # Determine whether a mutation is needed for this genotype:
    mutation = "none"
    mutentry = ""
    mutstart = 0
    mutend = 0
    regionoffset = 0
    regionstrand = ''
    inmuts = open(mutfile, "r")
    for line in inmuts:
        fields = line.split()
        if fields[3] == geno:
            mutation = fields[5]
            mutentry = fields[0] 
            mutstart = int(fields[1])
            mutend = int(fields[2])
        if fields[3] == "REGION":
            mutentry = fields[0] 
            regionoffset = int(fields[1])
            regionstart = regionoffset
            regionend = int(fields[2])
            regionstrand = fields[4]
    inmuts.close()

    # mutstart is zero-based start within AlphaThal region, regionoffset is zero-based
    # start of AlphaThal region in contig, so sum of mutstart and regionoffset is the
    # zero-based start of the deletion, in coordinates along the contig. First deleted
    # base is mutstart + 1 (one-based) or mutstart (zero-based)
    # mutend is one based, so after summing, mutend is one-based end of deletion in 
    # coordinates within the contig

    mutstart = mutstart + regionoffset
    mutend = mutend + regionoffset

    # if there is a deletion or duplication, the regionend value will be altered:
    if mutation == "deletion":
        regionend = regionend - (mutend - mutstart)
    if mutation == "duplication":
        regionend = regionend + (mutend - mutstart)

    print("Found mutation " + mutation + " with position " +  str(mutstart) + "-" + str(mutend) + " in region from " + str(regionstart) + "-" + str(regionend) )

    return Mutationdata(mutation, mutentry, mutstart, mutend, regionoffset, regionstart, regionend, regionstrand)

def truncateseq(inputseq, fiveprimeflank, threeprimeflank, capturestart, captureend, strand):
    print("Applying 5p buffer " + str(fiveprimeflank))
    print("Applying 3p buffer " + str(threeprimeflank))
    if strand == "+":
        startbuf = fiveprimeflank
        endbuf = threeprimeflank
    if strand == "-":
        startbuf = threeprimeflank
        endbuf = fiveprimeflank
    seqstart = capturestart - startbuf
    seqend = captureend + endbuf
    seqlength = len(inputseq)
    if seqstart < 0:
        seqstart = 0
        print("Only able to include " + str(capturestart) + " of five prime flank to the region of interest")
    if seqend > seqlength:
        seqend = seqlength
        print("Only able to include " + str(seqend - captureend) + " of three prime flank to the region of interest")
    print("Attempting to extract from  " + str(seqstart) + " to " + str(seqend))
    truncatedseq = inputseq[seqstart:seqend]

    return truncatedseq

with open(snakemake.log[0], "w") as f:
    sys.stderr = sys.stdout = f    
    genome_file = snakemake.output[0]
    match = re.search(r'^genomes/(\S{2})\_(\S{4})\_(\S{2})\_(\S{4})\.fasta$', genome_file)
    if match:

        sampledata = gatherdata(match)
        samples = sampledata.samples
        genotypes = sampledata.genotypes
        genomefiles = sampledata.genomefiles
        mutationfiles = sampledata.mutationfiles
        fivepgenomeregionbuffer = int(snakemake.config["fivepgenomeregionbuffer"])
        threepgenomeregionbuffer = int(snakemake.config["threepgenomeregionbuffer"])

        outgenome = open(genome_file, "w")
        for genomeindex in range(2):
            inputgenomefile = snakemake.config["genomedir"] + "/" + genomefiles[genomeindex]
            mutationfile = snakemake.config["mutationdir"] + "/" + mutationfiles[genomeindex]
            thisgeno = genotypes[genomeindex]

            mutdata = retrievemutdata(mutationfile, thisgeno)
            mutation = mutdata.mutation
            mutentry = mutdata.mutentry
            mutstart = mutdata.mutstart
            mutend = mutdata.mutend
            regionstrand = mutdata.regionstrand
            regionoffset = mutdata.regionoffset
            regionstart = mutdata.regionstart
            regionend = mutdata.regionend

            currentseqid = ''
            currentseq = ''
            startbuf = 0
            endbuf = 0

            fastagenome = pysam.Fastafile(inputgenomefile)
            contigseq = fastagenome.fetch(mutentry)
            print("Length of entry " + mutentry + ":" + str(len(contigseq)))
            if mutation == "deletion":
                currentseq = contigseq[0:mutstart] + contigseq[mutend:len(contigseq)]
            elif mutation == "duplication":
                currentseq = contigseq[0:mutend] + contigseq[mutstart:mutend] + contigseq[mutend:len(contigseq)]
            else:
                currentseq = contigseq[0:len(contigseq)]
            print("Length of mutated entry " + mutentry + ":" + str(len(currentseq)))
            if snakemake.config["fivepgenomeregionbuffer"] != "None":
                currentseq = truncateseq(currentseq, fivepgenomeregionbuffer, threepgenomeregionbuffer, regionstart, regionend, regionstrand)
            print(">" + mutentry, file=outgenome)
            print60(currentseq, outgenome)

            #ingenome = gzip.open(inputgenomefile, "r")
            #for line in ingenome:
                #line = str(line,'utf-8')
                #match = re.search(r'^>\s*(\S+)', line)
                #if match:
                    ## print current entry if there is one
                    #if len(currentseq) > 0:
                        ## handle case where entry contains our target region:
                        #if currentseqid == mutentry:
                            #print("Found mutation entry " + mutentry + " with length " + str(len(currentseq)))
                            #if mutation == "deletion":
                                #oneseq = currentseq.replace("\n", "")
                                #print("Length of entry " + mutentry + ":" + str(len(oneseq)))
                                #currentseq = oneseq[0:mutstart] + oneseq[mutend:len(oneseq)]
                                #print("Length of mutated entry " + mutentry + ":" + str(len(currentseq)))
                            #if mutation == "duplication":
                                #oneseq = currentseq.replace("\n", "")
                                #print("Length of entry " + mutentry + ":" + str(len(oneseq)))
                                #currentseq = oneseq[0:mutend] + oneseq[mutstart:mutend] + oneseq[mutend:len(oneseq)]
                                #print("Length of mutated entry " + mutentry + ":" + str(len(currentseq)))
                            #if snakemake.config["fivepgenomeregionbuffer"] != "None":
                                #currentseq = truncateseq(currentseq, fivepgenomeregionbuffer, threepgenomeregionbuffer, regionstart, regionend, regionstrand)
    #
                            #print(">" + currentseqid, file=outgenome)
                            #print60(currentseq, outgenome)
                        #else:
                            #if snakemake.config["fivepgenomeregionbuffer"] == "None":
                                #print(">" + currentseqid, file=outgenome)
                                #print(currentseq, file=outgenome, end="")
                            #
                    #currentseqid = match.group(1)
                    ##print("Found", currentseqid)
                    #currentseq = ''
                #else:
                    #currentseq = currentseq + line.strip()
            #ingenome.close()
            #if len(currentseq) > 0:
                #if currentseqid == mutentry:
                    #if mutation == "deletion":
                        ## delete appropriate sequence
                        #oneseq = currentseq.replace("\n", "")
                        #print("Length of entry" + mutentry + ":" + str(len(oneseq)))
                        #print("0 to " + str(mutstart) + ", " + str(len(oneseq)))
                        #currentseq = oneseq[0:mutstart] + oneseq[mutend:len(oneseq)]
                    #if mutation == "duplication":
                        #oneseq = currentseq.replace("\n", "")
                        #print("Length of entry" + mutentry + ":" + str(len(oneseq)))
                        #currentseq = oneseq[0:mutend] + oneseq[mutstart:mutend] + oneseq[mutend:len(oneseq)]
                        #print("Length of mutated entry" + mutentry + ":" + str(len(currentseq)))
                    #if snakemake.config["fivepgenomeregionbuffer"] != "None":
                        #currentseq = truncateseq(currentseq, fivepgenomeregionbuffer, threepgenomeregionbuffer, regionstart, regionend, regionstrand)
                    #print(">" + currentseqid, file=outgenome)
                    #print60(currentseq, outgenome)
                #else:
                    #if snakemake.config["fivepgenomeregionbuffer"] == "None":
                        #print(">" + currentseqid, file=outgenome)
                        #print(currentseq, file=outgenome, end="")
                        #
        outgenome.close()
    else:
        print("Couldn\'t parse filename " + genome_file)
Python pysam From line 1 of scripts/create_genome.py 
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import os
import re
import gzip
from collections import namedtuple

def retrieve_genotype(match):
    genolist = []
    genolist.append(match.group(2))
    genolist.append(match.group(4))

    return genolist

with open(snakemake.log[0], "w") as f:
    sys.stderr = sys.stdout = f

    # kmer count file has kmer counts from the simulated fastq file
    kmer_count_file = snakemake.input[0]

    # all kmer file establishes the order of the columns, so all sequence sets will generate the same columns in their feature files
    all_kmer_file = snakemake.input[1]

    # feature file will contain a column for each kmer with counts
    feature_file = snakemake.output[0]

    kmercounts = {}

    print("Opening " + kmer_count_file)
    with open(kmer_count_file, "r") as inkmercount_f:
        for line in inkmercount_f:
            line = line.strip()
            countmatch = re.search(r'^(\S+)\s(\d+)$', line)
            if countmatch:
                currentkmer = countmatch.group(1)
                currentcount = countmatch.group(2)
                kmercounts[currentkmer] = currentcount
                #print("Recording kmer " + currentkmer + " with count " + currentcount)
            else:
                print("Can\'t find kmer in line:\n" + line)

    print("Successfully read in simulated kmer counts from file " + kmer_count_file)

    # calculate total counts for this sample:
    # append normalized kmer counts to a list for printing:

    kmertotal = 0
    numkmers = 0   
    countlist = [] 
    with open(all_kmer_file, "r") as inallkmers_f:
        for line in inallkmers_f:
            line = line.strip()
            kmermatch = re.search(r'^(\S+)\s(\d+)$', line)
            if kmermatch:
                numkmers = numkmers + 1
                printkmer = kmermatch.group(1)
                if kmercounts.get(printkmer) == None:
                    countlist.append("0")
                else:
                    countlist.append(str(kmercounts[printkmer]))
                    kmertotal = kmertotal + int(kmercounts[printkmer])
            else:
                print("Can\'t find kmer in line:\n" + line)

        print("Normalizing")
        normcountlist = []
        for count in countlist:
            normcountlist.append(str(round(50.0*int(count)*numkmers/kmertotal)))
        normcountlist.append("Unknown")

    with open(feature_file, "w") as outfeature_f:
        featurestring = "\t".join(normcountlist)
        print(featurestring, file=outfeature_f)
Python From line 1 of scripts/create_test_featurefile.py 
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script:
    "scripts/create_genome.py"
SnakeMake From line 15 of workflow/Snakefile 
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shell:
    """
    for i in $(seq {wildcards.iteration}); do sleep 1; done
    art_illumina -ss HS25 -f {wildcards.coverage} -l {params.rl} -m {params.il} -s {params.ilsig} -i {input} -na -d {wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}. -o simreads/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}. > {log} 2>&1 
    """
SnakeMake From line 33 of workflow/Snakefile 
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shell:
    """
    meryl intersect [union-sum output features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration} [count simreads/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.1.fq output features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.1] [count simreads/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.2.fq output features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.2]] {params.kmerdb} output features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.targetkmercounts >>{log} 2>&1
    meryl print features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.targetkmercounts>{output} 2>>{log}
    rm -rf features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.targetkmercounts features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.1 features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}.2 features/{wildcards.samplegenotype}.{wildcards.coverage}x.{wildcards.iteration}
    """
SnakeMake Meryl From line 51 of workflow/Snakefile 
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shell:
    "meryl print {params.kmerdb} | awk 'NR==30*int(NR/30) {{print}}' > {output} 2>>{log}"
SnakeMake Meryl From line 67 of workflow/Snakefile 
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script:
    "scripts/create_featurefile.py"
SnakeMake From line 78 of workflow/Snakefile 
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shell:
    "cat {input} > {output}"
SnakeMake From line 88 of workflow/Snakefile 
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shell:
    "(awk '{{print $1}}' features/all_feature_kmers.txt | tr \"\n\" \"\t\"; echo \"Genotype\"; cat features/combined_feature_file.{wildcards.genotype}.noheader.txt ) > {output}"
SnakeMake From line 99 of workflow/Snakefile 
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shell:
    """
    meryl intersect [count testsamples/{wildcards.prefix}.fastq output testsamples/{wildcards.prefix}] {params.kmerdb} output testsamples/{wildcards.prefix}.targetkmercounts >>{log} 2>&1
    meryl print testsamples/{wildcards.prefix}.targetkmercounts>{output} 2>>{log}
    rm -rf testsamples/{wildcards.prefix}.targetkmercounts testsamples/{wildcards.prefix}
    """
SnakeMake Meryl From line 113 of workflow/Snakefile 
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script:
    "scripts/create_test_featurefile.py"
SnakeMake From line 128 of workflow/Snakefile
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Created: 1yr ago
Updated: 1yr ago
Maitainers: public
URL: https://github.com/nhansen/mlgenofeatures
Name: mlgenofeatures
Version: 1
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Copyright: Public Domain
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