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Snakefile
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Snakefile
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import os
from Bio import SeqIO
import re
import glob
import math
configfile: "config.yaml"
## input
fastq_dir = config["fastq_dir"]
samples,fq, = glob_wildcards(os.path.join(fastq_dir, "{sample}/{fq, .*.(fq|fq.gz|fastq|fastq.gz)}"))
uniq_samples = set(samples)
sample=[]
for i in uniq_samples:
sample.append(os.path.basename(i))
fastq_files, = glob_wildcards(os.path.join(fastq_dir, "{fastq_files, .*/.*.(fq|fq.gz|fastq|fastq.gz)}"))
ref = config["ref"]
chrom = []
# fasta_sequences = SeqIO.parse(open(ref),'fasta')
# for fasta in fasta_sequences:
# seqname = fasta.id
# if not re.match("Contig", seqname):
# chrom.append(seqname)
records = list(SeqIO.parse(open(ref),'fasta'))
idlist = list()
for r in records:
idlist.append(r.id)
chrom = []
for s in idlist:
if not re.match("Contig", s):
chrom.append(s)
## output
# chrom = {"Chr01", "Chr02", "Chr03", "Chr04", "Chr05", "Chr06", "Chr07", "Chr08", "Chr09", "Chr10", "Chr11"}
output_dir = config["output_dir"]
gatk_VF_opt = config["gatk_VariantFiltration"]["params"]
gatk_SV_opt = config["gatk_SelectVariants"]["params"]
vcftools_opt = config["vcftools"]["params"]
gatk_VF_suf = "" # config["gatk_VariantFiltration"]["suffix"]
gatk_SV_suf = "" # config["gatk_SelectVariants"]["suffix"]
vcftools_suf = "" # config["vcftools"]["suffix"]
filtered = ""
if gatk_VF_opt:
gatk_VF_suf = config["gatk_VariantFiltration"]["suffix"]
filtered += gatk_VF_suf
if gatk_SV_opt:
gatk_SV_suf = config["gatk_SelectVariants"]["suffix"]
filtered += gatk_SV_suf
if vcftools_opt:
vcftools_suf = config["vcftools"]["suffix"]
filtered += vcftools_suf
if gatk_VF_opt or gatk_SV_opt or vcftools_opt:
final_dir = "filtered_vcf_by_chrom"
else:
final_dir = "vcf_by_chrom"
container: "docker://continuumio/miniconda3:4.4.10"
## quality control before processing
# rule fastqc:
# input: os.path.join(output_dir, "fastqc/fastqc.html")
rule fastqc:
input: expand(os.path.join(fastq_dir, "{fastq_files}"), fastq_files = fastq_files)
output: os.path.join(output_dir, "fastqc/fastqc_final.html")
log: os.path.join(output_dir, "logs/fastqc/fastqc.log")
params:
opt = config["fastqc"]["params"]
threads: config["fastqc"]["threads"]
conda: "conda.yaml"
# singularity: singularity_img
shell:
"""
exec > >(tee {log}) 2>&1
outdir=$(dirname {output})
mkdir -p $outdir
fastqc -o $outdir -t {threads} -f fastq {input}
multiqc -o $outdir -n fastqc $outdir/*_fastqc.zip
"""
rule gbp_variantcalling:
input:
vcf_gz = expand(os.path.join(output_dir, "{final_dir}/all_final{filtered}_singletons.vcf.gz"), final_dir = final_dir, filtered = filtered),
vcf_tbi = expand(os.path.join(output_dir, "{final_dir}/all_final{filtered}_singletons.vcf.gz.tbi"), final_dir = final_dir, filtered = filtered),
# expand(os.path.join(output_dir, "{final_dir}/{chrom}{filtered}.vcf"), final_dir = final_dir, chrom = chrom, filtered = filtered)
## pre-processing if neccessary
# rule fastp
## variant calling from fastq
rule index_ref:
input: ref
output: multiext(ref, ".bwt", ".pac", ".ann", ".amb", ".sa") # bwt. pac, ann, amb, sa
log: os.path.join(output_dir, "logs/bwa_mem/index_ref.log")
shadow: "full"
conda: "conda.yaml"
shell:
"""
exec > >(tee {log}) 2>&1
bwa index {ref}
ref_name=$(basename -s .fasta {ref})
ref_dict="$(dirname {ref})/$ref_name.dict"
ref_fai="{ref}.fai"
if [[ ! -f $ref_dict || ! -f $ref_fai ]]
then
picard CreateSequenceDictionary -REFERENCE {ref} -OUTPUT $ref_dict
samtools faidx {ref}
fi
if [[ ! -f {ref}.fai ]]
then
samtools faidx {ref} --fai-idx {ref}.fai
fi
"""
def input_bwa_mem(wildcards):
# d,fq, = glob_wildcards(os.path.join(fastq_dir, "{d}/{wildcards.sample}/{fq, .*.(fq|fq.gz|fastq|fastq.gz)}"))
fq = glob.glob("{fastq_dir}/**/{sample}/*.f*".format(fastq_dir = fastq_dir, sample = wildcards.sample), recursive=True)
return fq
rule bwa_mem:
input:
fastq = input_bwa_mem,
# fastq = os.path.join(fastq_dir, "{sample}"),
ref_index = rules.index_ref.output
output: temp(os.path.join(output_dir, "bwa_mem/{sample}.sam"))
shadow: "full"
log: os.path.join(output_dir, "logs/bwa_mem/{sample}.log")
params: config["bwa_mem"]["params"]
threads: config["bwa_mem"]["threads"]
resources:
mem = config["bwa_mem"]["mem"]
conda: "conda.yaml"
# singularity: singularity_img
shell:
"""
exec > >(tee {log}) 2>&1
# fastq=$(find {input.fastq} -regex ".*\(1\|2\).\(fq.gz\|fastq.gz\|fq\|fastq\)" | xargs -n1 | sort | xargs)
echo "bwa mem -t {threads} {params} {ref} {input.fastq} > {output}"
bwa mem {ref} {input.fastq} -t {threads} {params} -R $(./read_group.sh {input.fastq}) > {output}
"""
rule picard_SortSam:
input: rules.bwa_mem.output
output:
bam = temp(os.path.join(output_dir, "sorted_bam/{sample}/{sample}_SortSam.bam")),
bai = temp(os.path.join(output_dir, "sorted_bam/{sample}/{sample}_SortSam.bai")),
shadow: "full"
log: os.path.join(output_dir, "logs/sorted_bam/picard_SortSam_{sample}.log")
params: config["picard_SortSam"]["params"]
resources:
mem = config["picard_SortSam"]["mem"]
conda: "conda.yaml"
shell:
"""
exec > >(tee {log}) 2>&1
picard SortSam -I {input} -O {output.bam} -CREATE_INDEX true {params}
"""
rule samtools_view:
input: rules.picard_SortSam.output.bam
output:
bam = temp(os.path.join(output_dir, "sorted_bam/{sample}/{sample}_samtoolsView.bam")),
bai = temp(os.path.join(output_dir, "sorted_bam/{sample}/{sample}_samtoolsView.bam.bai")),
shadow: "full"
log: os.path.join(output_dir, "logs/sorted_bam/samtoolsView_{sample}.log")
params: config["samtools_view"]["params"]
threads: config["samtools_view"]["threads"]
resources:
mem = config["samtools_view"]["mem"]
conda: "conda.yaml"
# singularity: singularity_img
shell:
"""
exec > >(tee {log}) 2>&1
samtools view {params} -@ {threads} -o {output.bam} {input}
samtools index {output.bam}
"""
rule MarkDuplicates:
input: rules.samtools_view.output.bam
output:
bam = os.path.join(output_dir, "sorted_bam/{sample}/{sample}_MarkDuplicate.bam"),
bai = os.path.join(output_dir, "sorted_bam/{sample}/{sample}_MarkDuplicate.bam.bai"),
sbi = os.path.join(output_dir, "sorted_bam/{sample}/{sample}_MarkDuplicate.bam.sbi"),
shadow: "full"
log: os.path.join(output_dir, "logs/sorted_bam/MarkDuplicate_{sample}.log")
params: config["MarkDuplicates"]["params"]
threads: config["MarkDuplicates"]["threads"]
resources:
mem = config["MarkDuplicates"]["mem"]
conda: "conda.yaml"
# singularity: singularity_img
shell:
"""
exec > >(tee {log}) 2>&1
rm -rf {output}.parts
ref_name=$(basename -s .fa {ref})
ref_dict="$(dirname {ref})/$ref_name.dict"
ref_fai="{ref}.fai"
if [[ ! -f $ref_dict || ! -f $ref_fai ]]
then
picard CreateSequenceDictionary -REFERENCE {ref} -OUTPUT $ref_dict
samtools faidx {ref}
fi
gatk MarkDuplicatesSpark -R {ref} -I {input} -O {output.bam} --spark-runner LOCAL
"""
rule HaplotypeCaller:
input: rules.MarkDuplicates.output.bam
output:
gvcf = os.path.join(output_dir, "HaplotypeCaller/{sample}.g.vcf"),
idx = os.path.join(output_dir, "HaplotypeCaller/{sample}.g.vcf.idx"),
shadow: "full"
log: os.path.join(output_dir, "logs/HaplotypeCaller/{sample}.log")
params: config["HaplotypeCaller"]["params"]
threads: config["HaplotypeCaller"]["threads"]
resources:
mem = config["HaplotypeCaller"]["mem"]
conda: "conda.yaml"
# singularity: singularity_img
shell:
"""
exec > >(tee {log}) 2>&1
gatk HaplotypeCaller -R {ref} -I {input} -O {output.gvcf} --native-pair-hmm-threads {threads} -ERC GVCF {params}
"""
GenomicsDBImport_input = ' -V '.join(expand(rules.HaplotypeCaller.output, sample = uniq_samples))
def GenomicsDBImport_intervals(wildcards):
chrid = wildcards.chrom
chridx = idlist.index(chrid)
size = 1e7
chrlen = len(records[chridx])
chr_itv = math.floor(chrlen/size)
if chrlen % size < 5e5:
chr_itv = chr_itv
else:
chr_itv += 1
GenomicsDBImport_intervals = ''
for i in range(0, chr_itv):
f = int((i * size) + 1)
if i < chr_itv -1:
l = int((i + 1) * size)
else:
l = chrlen
s = '-L {chrid}:{f}-{l} '.format(chrid=chrid, f=f, l=l)
GenomicsDBImport_intervals += s
return GenomicsDBImport_intervals
rule GenomicsDBImport:
input: expand(rules.HaplotypeCaller.output.gvcf, sample = set(sample))
output: temp(directory(os.path.join(output_dir, "gendb/{chrom}")))
shadow: "full"
log: os.path.join(output_dir, "logs/gendb/{chrom}.log")
params:
intervals = GenomicsDBImport_intervals,
ext_params = config["GenomicsDBImport"]["params"]
# threads: config["GenomicsDBImport"]["threads"]
resources:
mem = config["GenomicsDBImport"]["mem"]
conda: "conda.yaml"
# singularity: singularity_img
shell:
"""
exec > >(tee {log}) 2>&1
GenomicsDBImport_input=''
for f in {input}
do
GenomicsDBImport_input="$GenomicsDBImport_input -V $f"
done
gatk GenomicsDBImport $GenomicsDBImport_input --genomicsdb-workspace-path {output} --overwrite-existing-genomicsdb-workspace -imr OVERLAPPING_ONLY {params.intervals}{params.ext_params}
"""
# rule CombineGVCFs:
# input: expand(rules.HaplotypeCaller.output.gvcf, sample = sample)
# output:
# gvcf = os.path.join(output_dir, "vcf_by_chrom/combined.g.vcf"),
# idx = os.path.join(output_dir, "vcf_by_chrom/combined.g.vcf.idx"),
# shadow: "full"
# log: os.path.join(output_dir, "logs/vcf_by_chrom/CombineGVCFs.log")
# params: config["CombineGVCFs"]["params"]
# resources:
# mem = config["CombineGVCFs"]["mem"]
# conda: "conda.yaml"
# # singularity: singularity_img
# shell:
# """
# exec > >(tee {log}) 2>&1
# input=""
# for i in {input}; do input=$input' -V '$i; done
# gatk CombineGVCFs -R {ref} $input -O {output.gvcf} {params}
# """
# rule GenotypeGVCFs :
# input: rules.CombineGVCFs.output.gvcf
# output:
# gvcf = os.path.join(output_dir, "vcf_by_chrom/{chrom}.vcf"),
# idx = os.path.join(output_dir, "vcf_by_chrom/{chrom}.vcf.idx"),
# shadow: "full"
# log: os.path.join(output_dir, "logs/vcf_by_chrom/GenotypeGVCFs_{chrom}.log")
# params: config["GenotypeGVCFs"]["params"]
# resources:
# mem = config["GenotypeGVCFs"]["mem"]
# conda: "conda.yaml"
# # singularity: singularity_img
# shell:
# """
# exec > >(tee {log}) 2>&1
# gatk GenotypeGVCFs -R {ref} -V {input} -O {output.gvcf} {params} --intervals {wildcards.chrom}
# """
rule GenotypeGVCFs :
input: rules.GenomicsDBImport.output
output:
gvcf = os.path.join(output_dir, "vcf_by_chrom/{chrom}.vcf"),
idx = os.path.join(output_dir, "vcf_by_chrom/{chrom}.vcf.idx"),
shadow: "full"
log: os.path.join(output_dir, "logs/vcf_by_chrom/GenotypeGVCFs_{chrom}.log")
params: config["GenotypeGVCFs"]["params"]
resources:
mem = config["GenotypeGVCFs"]["mem"]
conda: "conda.yaml"
# singularity: singularity_img
shell:
"""
exec > >(tee {log}) 2>&1
cd $(dirname {input})
db=$(basename {input})
mkdir -p $(dirname {output.gvcf})
gatk GenotypeGVCFs -R {ref} -V gendb://$db -O {output.gvcf} {params}
"""
## variant filtration
rule filter_variants:
input: rules.GenotypeGVCFs.output.gvcf
output: os.path.join(output_dir, "filtered_vcf_by_chrom/{chrom}{filtered}_singletons.vcf".format(chrom = "{chrom}", filtered = filtered))
shadow: "full"
log: os.path.join(output_dir, "logs/filtered_vcf_by_chrom/{chrom}.log")
params:
gatk_VF_opt = gatk_VF_opt,
gatk_SV_opt = gatk_SV_opt,
vcftools_opt = vcftools_opt,
gatk_VF_suf = gatk_VF_suf,
gatk_SV_suf = gatk_SV_suf,
vcftools_suf = vcftools_suf,
variant_count = "variant_count.csv",
resources:
mem = config["filtration_mem"]
conda: "conda.yaml"
shell:
"""
exec > >(tee {log}) 2>&1
init_dir=$PWD
dir=$(dirname {output})
stats_file=$dir/variant_count.csv
if [[ ! -f $stats_file ]]
then
cp {params.variant_count} $dir/
echo -e "Filter,None,{gatk_VF_opt},{gatk_SV_opt},{vcftools_opt},singletons_doubletons" >> $stats_file
echo -e "Filename,None,{gatk_VF_suf},{gatk_SV_suf},{vcftools_suf},{vcftools_suf}_singletons" >> $stats_file
fi
raw_count=$(echo $(gatk CountVariants -V {input}) | sed 's/Tool returned://g')
in_name=$(basename {input} | sed 's/.vcf//')
input="{input}"
gatk_VF_opt="{params.gatk_VF_opt}"
if [[ ! -z $gatk_VF_opt ]]
then
echo -e "### filtering by gatk VariantFiltration: {params.gatk_VF_opt}"
gatk VariantFiltration -R {ref} -V $input -O $dir/$in_name"{params.gatk_VF_suf}.vcf" {params.gatk_VF_opt}
cd $dir
vcftools --vcf $in_name"{params.gatk_VF_suf}.vcf" --out $in_name"{params.gatk_VF_suf}" --remove-filtered-all --recode --recode-INFO-all
mv $in_name"{params.gatk_VF_suf}.recode.vcf" $in_name"{params.gatk_VF_suf}.vcf"
cd $init_dir
vf_count=$(echo $(gatk CountVariants -V $dir/$in_name"{params.gatk_VF_suf}.vcf") | sed 's/Tool returned://g')
input=$dir/$in_name"{params.gatk_VF_suf}.vcf"
in_name=$in_name"{params.gatk_VF_suf}"
else
vf_count=$raw_count
fi
gatk_SV_opt="{params.gatk_SV_opt}"
if [[ ! -z $gatk_SV_opt ]]
then
echo -e "### filtering by gatk SelectVariants: {params.gatk_SV_opt}"
gatk SelectVariants -R {ref} -V $input -O $dir/$in_name"{params.gatk_SV_suf}.vcf" {params.gatk_SV_opt}
sv_count=$(echo $(gatk CountVariants -V $dir/$in_name"{params.gatk_SV_suf}.vcf") | sed 's/Tool returned://g')
input=$dir/$in_name"{params.gatk_SV_suf}.vcf"
in_name=$in_name"{params.gatk_SV_suf}"
else
sv_count=$vf_count
fi
vcftools_opt="{params.vcftools_opt}"
if [[ ! -z $vcftools_opt ]]
then
echo -e "### filtering by vcftools: {params.vcftools_opt}"
cd $dir
vcftools --vcf $in_name".vcf" --out $in_name"{params.vcftools_suf}" --recode --recode-INFO-all {params.vcftools_opt}
mv $in_name"{params.vcftools_suf}.recode.vcf" $in_name"{params.vcftools_suf}.vcf"
vt_count=$(echo $(gatk CountVariants -V $in_name"{params.vcftools_suf}.vcf") | sed 's/Tool returned://g')
cd $init_dir
else
vt_count=$sv_count
fi
cd $dir
vcftools --singletons --vcf $in_name"{params.vcftools_suf}.vcf" --out {wildcards.chrom}
if [[ $(cat "{wildcards.chrom}.singletons" | wc -l ) != 1 ]]
then
echo "### filtering by vcftools: singletons and doubletons"
vcftools --vcf $in_name"{params.vcftools_suf}.vcf" --out $in_name"{params.vcftools_suf}_singletons" --exclude-positions "{wildcards.chrom}.singletons" --recode --recode-INFO-all
mv $in_name"{params.vcftools_suf}_singletons.recode.vcf" $in_name"{params.vcftools_suf}_singletons.vcf"
sgl_count=$(echo $(gatk CountVariants -V $in_name"{params.vcftools_suf}_singletons.vcf") | sed 's/Tool returned://g')
else
cp $in_name"{params.vcftools_suf}.vcf" $in_name"{params.vcftools_suf}_singletons.vcf"
sgl_count=$vt_count
fi
cd $init_dir
echo -e "{wildcards.chrom},$raw_count,$vf_count,$sv_count,$vt_count,$sgl_count" >> $stats_file
"""
rule concate_vcf:
input: expand(os.path.join(output_dir, "{final_dir}/{chrom}{filtered}_singletons.vcf"), final_dir = final_dir, chrom = chrom, filtered = filtered)
output:
vcf_gz = os.path.join(output_dir, "{final_dir}/all_final{filtered}.vcf.gz"),
vcf_tbi = os.path.join(output_dir, "{final_dir}/all_final{filtered}.vcf.gz.tbi"),
shadow: "full"
log: os.path.join(output_dir, "logs/{final_dir}/concate_vcf{filtered}.log")
conda: "conda.yaml"
shell:
"""
exec > >(tee {log}) 2>&1
out_vcf=$(echo {output.vcf_gz} | sed 's/\.gz//')
bcftools concat -o $out_vcf {input}
bgzip $out_vcf
tabix -p vcf {output.vcf_gz}
dir=$(dirname {output.vcf_gz})
stats_file=$dir/variant_count.csv
if [[ -f $stats_file ]]
then
append="Total"
for i in 2 3 4 5 6
do
t=$(tail -n +4 $stats_file | cut -d',' -f$i | awk '{{Total=Total+$1}} END{{print Total}}')
append=$append","$t
done
echo $append >> $stats_file
fi
"""
## stats
rule test:
shell:
"""
echo "{samples}"
"""
# to make rule graph: snakemake gbp_variantcalling -np --rulegraph | dot -Tsvg > dag.svg
# to make job graph: snakemake gbp_variantcalling -np --dag | dot -Tsvg > dag_job.svg