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Snakefile
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import os, sys
import pandas as pd
from modules.config_parsers import *
from modules.utils import *
configfile: "config.yaml"
log_dir = config["log_dir"]
ref_genome = config["ref_genome"]
snpEff_db = config["snpEff_db"]
# SAMPLES = ["A", "B", "C"]
# CONTROL = "CTRL"
# ALL = SAMPLES + [CONTROL]
datasets_tab = pd.read_table("data/datasets.tab", sep = "\t", comment='#')
# change library col type to string for wildcard constraints
datasets_tab['library'] = datasets_tab['library'].astype(str)
CONTROL, SAMPLES = get_control_samples(datasets_tab)
ALL = SAMPLES + [CONTROL]
wildcard_constraints:
sample = '|'.join([re.escape(x) for x in list(set(datasets_tab['sample']))]),
sample_ctrl = '|'.join([re.escape(x) for x in list(set(datasets_tab['sample']))]),
library = '|'.join([re.escape(x) for x in list(set(datasets_tab['library']))])
rule all:
input:
fastqc_raw_outputs(datasets_tab=datasets_tab),
expand("results/final/all_vs_{ctrl}_ann.vcf", ctrl=CONTROL),
expand("results/{sample}/variant_calling/{sample}_filt.vcf", sample=SAMPLES),
# mutant_ann_vcf = expand("annotations/{sample}_{ctrl}_ann.vcf", sample=SAMPLES, ctrl=CONTROL),
# control_filt_vcf = expand("variant_calling/{ctrl}_filt.vcf", ctrl=CONTROL),
rule symlink_libraries:
input:
R1 = lambda wildcards: expand(get_datasets_for_symlinks(datasets_tab, sample = wildcards.sample_ctrl, library = wildcards.library, d = "R1")),
R2 = lambda wildcards: expand(get_datasets_for_symlinks(datasets_tab, sample = wildcards.sample_ctrl, library = wildcards.library, d = "R2"))
output:
R1 = "data/reads/{sample_ctrl}_{library}.R1.fastq.gz",
R2 = "data/reads/{sample_ctrl}_{library}.R2.fastq.gz",
shell:
"""
cd data/reads/
ln -sf $(basename {input.R1}) $(basename {output.R1})
ln -sf $(basename {input.R2}) $(basename {output.R2})
"""
rule fastqc_raw:
input:
R1 = "data/reads/{sample_ctrl}_{library}.R1.fastq.gz",
R2 = "data/reads/{sample_ctrl}_{library}.R2.fastq.gz",
output:
html_report_R1 = "results/fastqc_raw/{sample_ctrl}_{library}.R1_fastqc.html",
html_report_R2 = "results/fastqc_raw/{sample_ctrl}_{library}.R2_fastqc.html",
params:
outDir = "results/fastqc_raw/",
threads:
2
# version:
# subprocess.check_output("fastqc -V", shell=True)
# message:
# "QC of raw read files {input} with {version}, {wildcards}"
log:
"logs/fastqc_raw/{sample_ctrl}_{library}.log"
#conda: "envs/environment.yaml"
shell:
"""
mkdir -p {params.outDir}
fastqc -t {threads} -o {params.outDir} {input} &> {log}
"""
rule trimmomatic:
""" QCing and cleaning reads """
params:
java_cmd = config['read_processing']['trimmomatic']['java_cmd'],
#jar_file = config['read_processing']['trimmomatic']['jar_file'],
mem = config['read_processing']['trimmomatic']['java_vm_mem'],
options = config['read_processing']['trimmomatic']['options'],
processing_options = config['read_processing']['trimmomatic']['processing_options'],
out1P = "data/reads_filtered/{sample_ctrl}_{library}_qc.R1.fastq.gz",
out2P = "data/reads_filtered/{sample_ctrl}_{library}_qc.R2.fastq.gz",
out1U = "data/reads_filtered/{sample_ctrl}_{library}_qc.1U.fastq.gz",
out2U = "data/reads_filtered/{sample_ctrl}_{library}_qc.2U.fastq.gz"
input:
R1 = "data/reads/{sample_ctrl}_{library}.R1.fastq.gz",
R2 = "data/reads/{sample_ctrl}_{library}.R2.fastq.gz"
output:
out1P = "data/reads_filtered/{sample_ctrl}_{library}_qc.R1.fastq.gz",
out2P = "data/reads_filtered/{sample_ctrl}_{library}_qc.R2.fastq.gz",
out1U = "data/reads_filtered/{sample_ctrl}_{library}_qc.U.fastq.gz",
threads:
config['read_processing']['trimmomatic']['threads']
# version:
# subprocess.check_output("trimmomatic -version", shell=True)
message:
"Filtering read dataset {wildcards.sample_ctrl}_{wildcards.library} with Trimmomatic. {wildcards}" # v{version}"
log:
log_dir + "/trimmomatic/{sample_ctrl}_{library}_trimmomatic.log"
#conda: "envs/environment.yaml"
run:
#trimmomatic_adapters_path = get_trimmomatic_adapters_path()
shell("export tap=$(which trimmomatic | sed 's/bin\/trimmomatic/share\/trimmomatic\/adapters\/TruSeq3-PE.fa/g'); trimmomatic PE {params.options} -threads {threads} {input.R1} {input.R2} {params.out1P} {params.out1U} {params.out2P} {params.out2U} ILLUMINACLIP:$tap:2:30:10 {params.processing_options} &> {log}")
shell("zcat {params.out1U} {params.out2U} | gzip > {output.out1U} && rm {params.out1U} {params.out2U}")
rule make_bwa_db:
input:
ref_fasta = "data/reference_genomes/{ref_genome}".format(ref_genome=ref_genome)
output:
bwa_index = "data/reference_genomes/{ref_genome}.amb".format(ref_genome=ref_genome)
run:
shell("bwa index {input.ref_fasta}")
rule map:
input:
f1 = "data/reads_filtered/{sample_ctrl}_{library}_qc.R1.fastq.gz",
f2 = "data/reads_filtered/{sample_ctrl}_{library}_qc.R2.fastq.gz",
bwa_index = "data/reference_genomes/{ref_genome}.amb".format(ref_genome=ref_genome)
# f1 = expand("data/filtered/{sample_ctrl}.R1.fastq.gz", sample_ctrl=ALL),
# f2 = expand("data/filtered/{sample_ctrl}.R2.fastq.gz", sample_ctrl=ALL)
output:
sam = temp("results/{sample_ctrl}/map/OUT_{sample_ctrl}_{library}/{sample}_{library}_OUT.sam.gz")
#sam = "results/{sample_ctrl}_{library}/map/{sample_ctrl}_{library}.sam"
params:
bwa_index = lambda wildcards, input: input.bwa_index.replace(".amb", ""),
threads = 4
run:
shell("bwa mem -t {params.threads} {params.bwa_index} {input.f1} {input.f2} | gzip - > {output.sam}")
rule sam2bam:
input:
sam = "results/{sample_ctrl}/map/OUT_{sample_ctrl}_{library}/{sample_ctrl}_{library}_OUT.sam.gz"
# sam = "alignment/{sample_ctrl}_{library}.sam"
output:
bam = temp("results/{sample_ctrl}/map/OUT_{sample_ctrl}_{library}/{sample_ctrl}_{library}_OUT-sorted.bam")
params:
TMP = check_tmp_dir("/tmp"),
uncompressed_sam = lambda wildcards: os.path.join(check_tmp_dir("/tmp"), "{}.sam".format(wildcards.sample_ctrl)),
first_bam = lambda wildcards: os.path.join(check_tmp_dir("/tmp"), "{}.bam".format(wildcards.sample_ctrl)),
sorted_bam = lambda wildcards: os.path.join(check_tmp_dir("/tmp"), "{}.sorted.bam".format(wildcards.sample_ctrl))
run:
shell("zcat {input.sam} > {params.uncompressed_sam} && samtools view -bS -o {params.first_bam} {params.uncompressed_sam}")
shell("samtools sort -T {params.TMP}/{wildcards.sample_ctrl} -o {params.sorted_bam} {params.first_bam}")
shell("samtools rmdup -s {params.sorted_bam} {output.bam}")
rule merge_bam:
input:
sorted_bams = lambda wildcards: get_sample_bamfiles(datasets_tab, res_dir="results", sample = wildcards.sample_ctrl)
output:
merged_bam = "results/{sample_ctrl}/map/{sample_ctrl}_OUT-sorted.bam",
merged_bam_index = "results/{sample_ctrl}/map/{sample_ctrl}_OUT-sorted.bam.bai"
#log: log_dir + "/{sample_ctrl}/{sample_ctrl}_merge_bam.log"
params:
TMP = check_tmp_dir("/tmp"),
temp_merged_bam = lambda wildcards, output: os.path.split(output.merged_bam)[1]
shell:
"""
# &> {log}
samtools merge -f {params.TMP}/{params.temp_merged_bam} {input}
samtools sort -T {params.TMP}/{wildcards.sample_ctrl} -o {output.merged_bam} {params.TMP}/{params.temp_merged_bam}
samtools index {output.merged_bam} {output.merged_bam_index}
"""
rule SNP_calling:
input:
bam = "results/{sample_ctrl}/map/{sample_ctrl}_OUT-sorted.bam"
output:
vcf = "results/{sample_ctrl}/variant_calling/{sample_ctrl}.vcf"
params:
ref = "data/reference_genomes/{ref_genome}".format(ref_genome=ref_genome)
run:
shell("bcftools mpileup -d 1000 -Ou -a FORMAT/AD,FORMAT/ADF,FORMAT/ADR,FORMAT/DP,FORMAT/SP,FORMAT/SCR,INFO/AD,INFO/ADF,INFO/ADR,INFO/SCR -f {params.ref} {input.bam} | \
bcftools call -mv > {output.vcf}")
# shell("samtools mpileup -Q 30 -C 50 -P Illumina \
# -t DP,DV,INFO/DPR,DP4,SP,DV \
# -Buf {params.ref} {input.bam} \
# | bcftools view -vcg --types snps > {output.vcf}")
rule filter_SNPs:
input:
vcf = "results/{sample_ctrl}/variant_calling/{sample_ctrl}.vcf"
output:
vcf = "results/{sample_ctrl}/variant_calling/{sample_ctrl}_filt.vcf"
run:
filter_vcf(input.vcf, output.vcf)
rule get_mutant_specific_SNPs:
input:
mutant_snps = "results/{sample}/variant_calling/{sample}_filt.vcf",
control_snps = expand("results/{ctrl}/variant_calling/{ctrl}_filt.vcf", ctrl=CONTROL)
output:
vcf = "results/{sample}/variant_calling/{sample}_{ctrl}_filt.vcf.gz"
run:
shell("subtractBed -header -a {input.mutant_snps} -b {input.control_snps} | bgzip -c > {output.vcf}")
rule bgzip_ctrl:
input:
vcf_ctrl = "results/{ctrl}/variant_calling/{ctrl}_filt.vcf"
output:
vcf_ctrl = "results/{ctrl}/variant_calling/{ctrl}_filt.vcf.gz",
vcf_ctrl_index = "results/{ctrl}/variant_calling/{ctrl}_filt.vcf.gz.csi",
run:
shell("bgzip < {input.vcf_ctrl} > {output.vcf_ctrl}")
shell("bcftools index -f -o {output.vcf_ctrl_index} {output.vcf_ctrl}")
rule index_VCF:
input:
single_vcf = "results/{sample}/variant_calling/{sample}_{ctrl}_filt.vcf.gz",
output:
index_vcf = "results/{sample}/variant_calling/{sample}_{ctrl}_filt.vcf.gz.csi"
#conda: "envs/bcftools.yaml"
message: "Compressing and indexing {input.single_vcf}"
run:
shell("bcftools index -f -o {output.index_vcf} {input.single_vcf}")
rule merge_mutant_specific_SNPs:
input:
vcf = expand("results/{sample}/variant_calling/{sample}_{ctrl}_filt.vcf.gz", sample=SAMPLES, ctrl=CONTROL),
index_vcf = expand("results/{sample}/variant_calling/{sample}_{ctrl}_filt.vcf.gz.csi", sample=SAMPLES, ctrl=CONTROL),
vcf_ctrl = "results/{ctrl}/variant_calling/{ctrl}_filt.vcf.gz"
output:
merged_vcf = "results/final/all_vs_{ctrl}.vcf"
run:
shell("bcftools merge {input.vcf_ctrl} {input.vcf} -O v -o {output.merged_vcf}")
rule annotate_mutant_specific_SNPs:
input:
vcf = "results/final/all_vs_{ctrl}.vcf"
output:
vcf = "results/final/all_vs_{ctrl}_ann.vcf"
params: snpEff_db = snpEff_db
run:
shell("snpEff {params.snpEff_db} {input.vcf} > {output.vcf}")