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How to use output_dir method in SeleniumLibrary

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urmo_imputation_hg38.smk

Source:urmo_imputation_hg38.smk

1#!/usr/bin/env python2shell.executable('bash')3# Converts BIM to BED and converts the BED file via CrossMap.4# Finds excluded SNPs and removes them from the original plink file.5# Then replaces the BIM with CrossMap's output.6rule crossmap:7    input:8        pgen = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset.pgen",9        psam = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset.psam",10        pvar = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset.pvar"11    output:12        bed = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink.bed",13        bim = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink.bim",14        fam = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink.fam",15        inbed = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmap_input.bed",16        outbed = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmap_output.bed",17        excluded_ids = output_dict["output_dir"] + "/crossmapped/{ancestry}_excluded_ids.txt"18    resources:19        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["crossmap_memory"],20        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["crossmap_memory"]21    threads:22        imputation_dict["crossmap_threads"]23    params:24        bind = input_dict["bind_paths"],25        sif = input_dict["singularity_image"],26        in_plink = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset",27        out = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink",28        chain_file = "/opt/GRCh37_to_GRCh38.chain"29    shell:30        """31        singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}{{print $1,$2,$2+1,$3,$4,$5}}' {input.pvar} > {output.inbed}32        singularity exec --bind {params.bind} {params.sif} CrossMap.py bed {params.chain_file} {output.inbed} {output.outbed}33        singularity exec --bind {params.bind} {params.sif} awk '{{print $4}}' {output.outbed}.unmap > {output.excluded_ids}34        singularity exec --bind {params.bind} {params.sif} plink2 --pfile {params.in_plink} --exclude {output.excluded_ids} --make-bed --output-chr MT --out {params.out}35        singularity exec --bind {params.bind} {params.sif} awk -F'\t' 'BEGIN {{OFS=FS}} {{print $1,$4,0,$2,$6,$5}}' {output.outbed} > {output.bim}36        """37rule sort_bed:38    input:39        pgen = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink.bed",40        psam = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink.bim",41        pvar = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink.fam"42    output:43        bed = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted.bed",44        bim = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted.bim",45        fam = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted.fam"46    resources:47        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["sort_bed_memory"],48        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["sort_bed_memory"]49    threads:50        imputation_dict["sort_bed_threads"]51    params:52        bind = input_dict["bind_paths"],53        sif = input_dict["singularity_image"],54        infile = output_dict["output_dir"] + "/crossmapped/{ancestry}_crossmapped_plink",55        out = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted"56    shell:57        """58        singularity exec --bind {params.bind} {params.sif} plink2 --bfile {params.infile} --make-bed --max-alleles 2 --output-chr MT --out {params.out}59        """60rule harmonize_hg38:61    input:62        bed = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted.bed",63        bim = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted.bim",64        fam = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted.fam",65        vcf = vcf_dir + "/30x-GRCh38_NoSamplesSorted.vcf.gz",66        index = vcf_dir + "/30x-GRCh38_NoSamplesSorted.vcf.gz.tbi"67    output:68        bed = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}.bed",69        bim = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}.bim",70        fam = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}.fam"71    resources:72        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["harmonize_hg38_memory"],73        java_mem = lambda wildcards, attempt: attempt * imputation_dict["harmonize_hg38_java_memory"],74        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["harmonize_hg38_memory"]75    threads:76        imputation_dict["harmonize_hg38_threads"]77    params:78        bind = input_dict["bind_paths"],79        sif = input_dict["singularity_image"],80        infile = output_dict["output_dir"] + "/crossmapped_sorted/{ancestry}_crossmapped_sorted",81        out = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}",82        jar = "/opt/GenotypeHarmonizer-1.4.23/GenotypeHarmonizer.jar"83    shell:84        """85        singularity exec --bind {params.bind} {params.sif} java -Xmx{resources.java_mem}g -jar {params.jar}\86            --input {params.infile}\87            --inputType PLINK_BED\88            --ref {input.vcf}\89            --refType VCF\90            --update-id\91            --output {params.out}92        """93rule plink_to_vcf:94    input:95        bed = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}.bed",96        bim = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}.bim",97        fam = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}.fam"98    output:99        data_vcf_gz = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}_harmonised_hg38.vcf.gz",100        index = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}_harmonised_hg38.vcf.gz.csi"101    resources:102        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["plink_to_vcf_memory"],103        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["plink_to_vcf_memory"]104    threads:105        imputation_dict["plink_to_vcf_threads"]106    params:107        bind = input_dict["bind_paths"],108        sif = input_dict["singularity_image"],109        infile = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}",110        out = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}_harmonised_hg38"111    shell:112        """113        singularity exec --bind {params.bind} {params.sif} plink2 --bfile {params.infile} --recode vcf id-paste=iid --chr 1-22 --out {params.out}114        singularity exec --bind {params.bind} {params.sif} bgzip {params.out}.vcf115        singularity exec --bind {params.bind} {params.sif} bcftools index {output.data_vcf_gz}116        """117rule vcf_fixref_hg38:118    input:119        fasta = fasta,120        vcf = vcf_dir + "/30x-GRCh38_NoSamplesSorted.vcf.gz",121        index = vcf_dir + "/30x-GRCh38_NoSamplesSorted.vcf.gz.tbi",122        data_vcf = output_dict["output_dir"] + "/harmonize_hg38/{ancestry}_harmonised_hg38.vcf.gz"123    output:124        vcf = output_dict["output_dir"] + "/vcf_fixref_hg38/{ancestry}_fixref_hg38.vcf.gz",125        index = output_dict["output_dir"] + "/vcf_fixref_hg38/{ancestry}_fixref_hg38.vcf.gz.csi"126    resources:127        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["vcf_fixref_hg38_memory"],128        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["vcf_fixref_hg38_memory"]129    threads:130        imputation_dict["vcf_fixref_hg38_threads"]131    params:132        bind = input_dict["bind_paths"],133        sif = input_dict["singularity_image"]134    shell:135        """136        singularity exec --bind {params.bind} {params.sif} bcftools +fixref {input.data_vcf} -- -f {input.fasta} -i {input.vcf} | \137        singularity exec --bind {params.bind} {params.sif} bcftools norm --check-ref x -f {input.fasta} -Oz -o {output.vcf}138        #Index139        singularity exec --bind {params.bind} {params.sif} bcftools index {output.vcf}140        """141rule filter_preimpute_vcf:142    input:143        vcf = output_dict["output_dir"] + "/vcf_fixref_hg38/{ancestry}_fixref_hg38.vcf.gz"144    output:145        tagged_vcf = output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_tagged.vcf.gz",146        filtered_vcf = output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_filtered.vcf.gz",147        filtered_index = output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_filtered.vcf.gz.csi"148    resources:149        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["filter_preimpute_vcf_memory"],150        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["filter_preimpute_vcf_memory"]151    threads:152        imputation_dict["filter_preimpute_vcf_threads"]153    params:154        bind = input_dict["bind_paths"],155        sif = input_dict["singularity_image"],156        maf = lambda wildcards: float(maf_df["MAF"][maf_df.Ancestry == wildcards.ancestry].values),157        missing = imputation_dict["snp_missing_pct"],158        hwe = imputation_dict["snp_hwe"]159    shell:160        """161        #Add tags162        singularity exec --bind {params.bind} {params.sif} bcftools +fill-tags {input.vcf} -Oz -o {output.tagged_vcf}163        #Filter rare and non-HWE variants and those with abnormal alleles and duplicates164        singularity exec --bind {params.bind} {params.sif} bcftools filter -i 'INFO/HWE > {params.hwe} & F_MISSING < {params.missing} & MAF[0] > {params.maf}' {output.tagged_vcf} |\165        singularity exec --bind {params.bind} {params.sif} bcftools filter -e 'REF="N" | REF="I" | REF="D"' |\166        singularity exec --bind {params.bind} {params.sif} bcftools filter -e "ALT='.'" |\167        singularity exec --bind {params.bind} {params.sif} bcftools norm -d all |\168        singularity exec --bind {params.bind} {params.sif} bcftools norm -m+any |\169        singularity exec --bind {params.bind} {params.sif} bcftools view -m2 -M2 -Oz -o {output.filtered_vcf}170        #Index the output file171        singularity exec --bind {params.bind} {params.sif} bcftools index {output.filtered_vcf}172        """173rule het:174    input:175        vcf = output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_filtered.vcf.gz",176    output:177        tmp_vcf = temp(output_dict["output_dir"] + "/het/{ancestry}_filtered_temp.vcf"),178        inds = output_dict["output_dir"] + "/het/{ancestry}_het_failed.inds",179        het = output_dict["output_dir"] + "/het/{ancestry}_het.het",180        passed = output_dict["output_dir"] + "/het/{ancestry}_het_passed.inds",181        passed_list = output_dict["output_dir"] + "/het/{ancestry}_het_passed.txt"182    resources:183        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["het_memory"],184        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["het_memory"]185    threads: imputation_dict["het_threads"]186    params:187        het_base = output_dict["output_dir"] + "/het/{ancestry}_het",188        script = "/opt/WG1-pipeline-QC/Imputation/scripts/filter_het.R",189        bind = input_dict["bind_paths"],190        hwe = output_dict["output_dir"] + "/hwe/{ancestry}_hwe",191        out = output_dict["output_dir"] + "/het/{ancestry}_het",192        sif = input_dict["singularity_image"],193    shell:194        """195        singularity exec --bind {params.bind} {params.sif} gunzip -c {input.vcf} | sed 's/^##fileformat=VCFv4.3/##fileformat=VCFv4.2/' > {output.tmp_vcf}196        singularity exec --bind {params.bind} {params.sif} vcftools --vcf {output.tmp_vcf} --het --out {params.het_base}197        singularity exec --bind {params.bind} {params.sif} Rscript {params.script} {output.het} {output.inds} {output.passed} {output.passed_list}198        """199rule het_filter:200    input:201        passed_list = output_dict["output_dir"] + "/het/{ancestry}_het_passed.txt",202        vcf = output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_filtered.vcf.gz"203    output:204        vcf = output_dict["output_dir"] + "/het_filter/{ancestry}_het_filtered.vcf.gz",205        index = output_dict["output_dir"] + "/het_filter/{ancestry}_het_filtered.vcf.gz.csi"206    resources:207        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["het_filter_memory"],208        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["het_filter_memory"]209    threads: imputation_dict["het_filter_threads"]210    params:211        bind = input_dict["bind_paths"],212        hwe = output_dict["output_dir"] + "/hwe/{ancestry}_hwe",213        out = output_dict["output_dir"] + "/het_filter/{ancestry}_het_filter",214        sif = input_dict["singularity_image"]215    shell:216        """217        singularity exec --bind {params.bind} {params.sif} bcftools view -S {input.passed_list} {input.vcf} -Oz -o {output.vcf}218        #Index the output file219        singularity exec --bind {params.bind} {params.sif} bcftools index {output.vcf}220        """221rule calculate_missingness:222    input:223        filtered_vcf = output_dict["output_dir"] + "/het_filter/{ancestry}_het_filtered.vcf.gz",224        filtered_index = output_dict["output_dir"] + "/het_filter/{ancestry}_het_filtered.vcf.gz.csi"225    output:226        tmp_vcf = temp(output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_het_filtered.vcf"),227        miss = output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_genotypes.imiss",228        individuals = output_dict["output_dir"] + "/genotype_donor_annotation/{ancestry}_individuals.tsv"229    resources:230        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["calculate_missingness_memory"],231        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["calculate_missingness_memory"]232    threads:233        imputation_dict["calculate_missingness_threads"]234    params:235        bind = input_dict["bind_paths"],236        sif = input_dict["singularity_image"],237        out = output_dict["output_dir"] + "/filter_preimpute_vcf/{ancestry}_genotypes"238    shell:239        """240        singularity exec --bind {params.bind} {params.sif} gunzip -c {input.filtered_vcf} | sed 's/^##fileformat=VCFv4.3/##fileformat=VCFv4.2/' > {output.tmp_vcf}241        singularity exec --bind {params.bind} {params.sif} vcftools --gzvcf {output.tmp_vcf} --missing-indv --out {params.out}242        singularity exec --bind {params.bind} {params.sif} bcftools query -l {input.filtered_vcf} >> {output.individuals}243        """244rule split_by_chr:245    input:246        filtered_vcf = output_dict["output_dir"] + "/het_filter/{ancestry}_het_filtered.vcf.gz",247        filtered_index = output_dict["output_dir"] + "/het_filter/{ancestry}_het_filtered.vcf.gz.csi"248    output:249        vcf = output_dict["output_dir"] + "/split_by_chr/{ancestry}_chr_{chr}.vcf.gz",250        index = output_dict["output_dir"] + "/split_by_chr/{ancestry}_chr_{chr}.vcf.gz.csi"251    resources:252        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["split_by_chr_memory"],253        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["split_by_chr_memory"]254    threads:255        imputation_dict["split_by_chr_threads"]256    params:257        bind = input_dict["bind_paths"],258        sif = input_dict["singularity_image"]259    shell:260        """261        singularity exec --bind {params.bind} {params.sif} bcftools view -r {wildcards.chr} {input.filtered_vcf} -Oz -o {output.vcf}262        singularity exec --bind {params.bind} {params.sif} bcftools index {output.vcf}263        """264rule eagle_prephasing:265    input:266        vcf = output_dict["output_dir"] + "/split_by_chr/{ancestry}_chr_{chr}.vcf.gz",267        map_file = genetic_map,268        phasing_file = phasing_dir + "/chr{chr}.bcf"269    output:270        vcf = output_dict["output_dir"] + "/eagle_prephasing/{ancestry}_chr{chr}_phased.vcf.gz"271    resources:272        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["eagle_prephasing_memory"],273        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["eagle_prephasing_memory"]274    threads: imputation_dict["eagle_prephasing_threads"]275    params:276        bind = input_dict["bind_paths"],277        sif = input_dict["singularity_image"],278        out = output_dict["output_dir"] + "/eagle_prephasing/{ancestry}_chr{chr}_phased"279    shell:280        """281        singularity exec --bind {params.bind} {params.sif} eagle --vcfTarget={input.vcf} \282            --vcfRef={input.phasing_file} \283            --geneticMapFile={input.map_file} \284            --chrom={wildcards.chr} \285            --outPrefix={params.out} \286            --numThreads={threads}287        """288rule minimac_imputation:289    input:290        vcf = output_dict["output_dir"] + "/eagle_prephasing/{ancestry}_chr{chr}_phased.vcf.gz",291        impute_file = impute_dir + "/chr{chr}.m3vcf.gz"292    output:293        output_dict["output_dir"] + "/minimac_imputed/{ancestry}_chr{chr}.dose.vcf.gz"294    resources:295        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["minimac_imputation_memory"],296        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["minimac_imputation_memory"]297    threads:298        imputation_dict["minimac_imputation_threads"]299    params:300        bind = input_dict["bind_paths"],301        sif = input_dict["singularity_image"],302        out = output_dict["output_dir"] + "/minimac_imputed/{ancestry}_chr{chr}",303        minimac4 = "/opt/bin/minimac4",304        chunk_length = imputation_dict["chunk_length"]305    shell:306        """307        singularity exec --bind {params.bind} {params.sif} {params.minimac4} --refHaps {input.impute_file} \308            --haps {input.vcf} \309            --prefix {params.out} \310            --format GT,DS,GP \311            --noPhoneHome \312            --cpus {threads} \313            --ChunkLengthMb {params.chunk_length}314        """315rule combine_vcfs_ancestry:316    input:317        vcfs = lambda wildcards: expand(output_dict["output_dir"] + "/minimac_imputed/{ancestry}_chr{chr}.dose.vcf.gz", chr = chromosomes, ancestry = ancestry_subsets)318    output:319        combined = output_dict["output_dir"] + "/vcf_merged_by_ancestries/{ancestry}_imputed_hg38.vcf.gz",320        ind = output_dict["output_dir"] + "/vcf_merged_by_ancestries/{ancestry}_imputed_hg38.vcf.gz.csi"321    resources:322        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["combine_vcfs_ancestry_memory"],323        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["combine_vcfs_ancestry_memory"]324    threads: imputation_dict["combine_vcfs_ancestry_threads"]325    params:326        sif = input_dict["singularity_image"],327        bind = input_dict["bind_paths"],328        files_begin = output_dict["output_dir"] + "/minimac_imputed/{ancestry}_chr*.dose.vcf.gz"329    shell:330        """331        singularity exec --bind {params.bind} {params.sif} bcftools concat -Oz {params.files_begin} > {output.combined}332        singularity exec --bind {params.bind} {params.sif} bcftools index {output.combined}333        """334rule combine_vcfs_all:335    input:336        vcfs = lambda wildcards: expand(output_dict["output_dir"] + "/vcf_merged_by_ancestries/{ancestry}_imputed_hg38.vcf.gz", ancestry = ancestry_subsets)337    output:338        combined = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38.vcf.gz",339        ind = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38.vcf.gz.csi"340    resources:341        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["combine_vcfs_memory"],342        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["combine_vcfs_memory"]343    threads: imputation_dict["combine_vcfs_threads"]344    params:345        sif = input_dict["singularity_image"],346        bind = input_dict["bind_paths"],347    shell:348        """349        if [[ $(ls -l {input.vcfs} | wc -l) > 1 ]]350        then351            singularity exec --bind {params.bind} {params.sif} bcftools merge -Oz {input.vcfs} > {output.combined}352        else353            cp {input.vcfs} {output.combined}354        fi355        singularity exec --bind {params.bind} {params.sif} bcftools index {output.combined}356        """357rule filter4demultiplexing:358    input:359        output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38.vcf.gz"360    output:361        info_filled = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_info_filled.vcf.gz",362        qc_filtered = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_R2_0.3_MAF0.05.vcf.gz",363        location_filtered = temp(output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_R2_0.3_MAF0.05_exons.recode.vcf"),364        complete_cases = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_R2_0.3_MAF0.05_exons_complete_cases.recode.vcf"365    resources:366        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["filter4demultiplexing_memory"],367        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["filter4demultiplexing_memory"]368    threads: imputation_dict["filter4demultiplexing_threads"]369    params:370        sif = input_dict["singularity_image"],371        bind = input_dict["bind_paths"],372        out = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_R2_0.3_MAF0.05_exons",373        complete_out = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_R2_0.3_MAF0.05_exons_complete_cases",374        bed = "/opt/hg38exonsUCSC.bed"375    shell:376        """377        ##### Add all the info fields378        singularity exec --bind {params.bind} {params.sif} bcftools +fill-tags -Oz --output {output.info_filled} {input}379        ##### Filter the Imputed SNP Genotype by Minor Allele Frequency (MAF) and INFO scores #####380        singularity exec --bind {params.bind} {params.sif} bcftools filter --include 'MAF>=0.05 & R2>=0.3' -Oz --output {output.qc_filtered} {output.info_filled}381        singularity exec --bind {params.bind} {params.sif} vcftools \382            --gzvcf {output.qc_filtered} \383            --max-alleles 2 \384            --remove-indels \385            --bed {params.bed} \386            --recode \387            --recode-INFO-all \388            --out {params.out}389        singularity exec --bind {params.bind} {params.sif} vcftools --recode --recode-INFO-all --vcf {output.location_filtered} --max-missing 1 --out {params.complete_out}390        """391rule sort4demultiplexing:392    input:393        complete_cases = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_R2_0.3_MAF0.05_exons_complete_cases.recode.vcf"394    output:395        complete_cases_sorted = output_dict["output_dir"] + "/vcf_4_demultiplex/imputed_hg38_R2_0.3_MAF0.05_exons_sorted.vcf"396    resources:397        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["sort4demultiplexing_memory"],398        java_mem = lambda wildcards, attempt: attempt * imputation_dict["sort4demultiplexing_java_memory"],399        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["sort4demultiplexing_memory"]400    threads: imputation_dict["sort4demultiplexing_threads"]401    params:402        sif = input_dict["singularity_image"],403        bind = input_dict["bind_paths"]404    shell:405        """406        singularity exec --bind {params.bind} {params.sif} java -Xmx{resources.java_mem}g -Xms{resources.java_mem}g -jar /opt/picard/build/libs/picard.jar SortVcf \407            I={input.complete_cases} \408            O={output.complete_cases_sorted}409        """410rule count_snps:411    input:412        info_filled = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_info_filled.vcf.gz",413        qc_filtered = output_dict["output_dir"] + "/vcf_all_merged/imputed_hg38_R2_0.3_MAF0.05.vcf.gz",414        complete_cases_sorted = output_dict["output_dir"] + "/vcf_4_demultiplex/imputed_hg38_R2_0.3_MAF0.05_exons_sorted.vcf"415    output:416        report(output_dict["output_dir"] + "/metrics/Number_SNPs.png", category = "SNP Numbers", caption = "../report_captions/counts_snps.rst")417    resources:418        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["count_snps_memory"],419        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["count_snps_memory"]420    threads: imputation_dict["count_snps_threads"]421    params:422        sif = input_dict["singularity_image"],423        bind = input_dict["bind_paths"],424        basedir = output_dict["output_dir"],425        outdir = output_dict["output_dir"] + "/metrics/",426        script = "/opt/WG1-pipeline-QC/Imputation/scripts/SNP_numbers.R"427    shell:428        """429        singularity exec --bind {params.bind} {params.sif} Rscript {params.script} {params.basedir} {params.outdir}430        """431rule genotype_donor_annotation:432    input:433        individuals = lambda wildcards: expand(output_dict["output_dir"] + "/genotype_donor_annotation/{ancestry}_individuals.tsv", ancestry = ancestry_subsets),434        updated_psam = output_dict["output_dir"] + "/update_sex_ancestry/update_sex.psam"435    output:436        out_temp = temp(output_dict["output_dir"] + "/genotype_donor_annotation/genotype_donor_annotation_temp.tsv"),437        combined_individuals = output_dict["output_dir"] + "/genotype_donor_annotation/combined_individuals.tsv",438        final = output_dict["output_dir"] + "/genotype_donor_annotation/genotype_donor_annotation.tsv",439    resources:440        mem_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["genotype_donor_annotation_memory"],441        disk_per_thread_gb=lambda wildcards, attempt: attempt * imputation_dict["genotype_donor_annotation_memory"]442    threads: imputation_dict["genotype_donor_annotation_threads"]443    params:444        bind = input_dict["bind_paths"],445        sif = input_dict["singularity_image"],446    shell:447        """448        singularity exec --bind {params.bind} {params.sif} cut -f2,5- {input.updated_psam} | awk 'NR<2{{print $0;next}}{{print $0| "sort -k1,1"}}' > {output.out_temp}449        singularity exec --bind {params.bind} {params.sif} cat {input.individuals} >> {output.combined_individuals}450        singularity exec --bind {params.bind} {params.sif} sed -i '1 i\IID' {output.combined_individuals}451        singularity exec --bind {params.bind} {params.sif} awk -F"\t" 'NR==FNR {{a[$1]; next}} $1 in a' {output.combined_individuals} {output.out_temp} | awk 'BEGIN{{FS=OFS="\t"}}{{sub("1","M",$2);print}}' | awk 'BEGIN{{FS=OFS="\t"}}{{sub("2","F",$2);print}}' > {output.final}452        singularity exec --bind {params.bind} {params.sif} sed -i 's/^IID\tSEX\tProvided_Ancestry/donor_id\tsex\tethnicity_super_population/g' {output.final}453        singularity exec --bind {params.bind} {params.sif} sed -i 's/$/\tsceQTL-Gen_hg38_imputation_pipeline\t1000g_30x_GRCh38_ref/' {output.final}454        singularity exec --bind {params.bind} {params.sif} sed -i '1s/SangerImputationServer/imputation_method/g' {output.final}455        singularity exec --bind {params.bind} {params.sif} sed -i '1s/1000g_30x_GRCh38_ref/imputation_reference/g' {output.final}...

plink_gender_ancestry_QC.smk

Source:plink_gender_ancestry_QC.smk

1#!/usr/bin/env python2shell.executable('bash')3rule indiv_missingness:4    input:5        pgen = pgen,6        pvar = pvar,7        psam = psam,8    output:9        bed = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.pgen",10        bim = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.pvar",11        fam = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.psam",12    resources:13        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["indiv_missingness_memory"],14        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["indiv_missingness_memory"]15    threads: plink_gender_ancestry_QC_dict["indiv_missingness_threads"]16    params:17       bind = input_dict["bind_paths"],18       infile = re.sub(".psam", "", psam),19       out = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness",20       mind = plink_gender_ancestry_QC_dict["indiv_missingness_mind"],21       sif = input_dict["singularity_image"]22    shell:23        """24        singularity exec --bind {params.bind} {params.sif} echo {params.infile}25        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} \26            --pfile {params.infile} \27            --make-pgen 'psam-cols='fid,parents,sex,phenos \28            --mind {params.mind} \29            --out {params.out}30        """31rule check_sex:32    input:33        bed = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.pgen",34        bim = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.pvar",35        fam = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.psam",36    output:37        bed = output_dict["output_dir"] + "/check_sex/check_sex.bed",38        bim = output_dict["output_dir"] + "/check_sex/check_sex.bim",39        fam = output_dict["output_dir"] + "/check_sex/check_sex.fam",40        hh = output_dict["output_dir"] + "/check_sex/check_sex.hh",41        log = output_dict["output_dir"] + "/check_sex/check_sex.log",42        nosex = output_dict["output_dir"] + "/check_sex/check_sex.nosex",43        sexcheck = output_dict["output_dir"] + "/check_sex/check_sex.sexcheck",44        sexcheck_tab = output_dict["output_dir"] + "/check_sex/check_sex.sexcheck.tsv"45    resources:46        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["check_sex_memory"],47        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["check_sex_memory"]48    threads: plink_gender_ancestry_QC_dict["check_sex_threads"]49    params:50        bind = input_dict["bind_paths"],51        infile = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness",52        out = output_dict["output_dir"] + "/check_sex/check_sex",53        sif = input_dict["singularity_image"]54    shell:55        """56        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile} --make-bed --max-alleles 2 --out {params.out}57        singularity exec --bind {params.bind} {params.sif} plink --threads {threads} --bfile {params.out} --check-sex --out {params.out}58        singularity exec --bind {params.bind} {params.sif} touch {output.nosex}59        singularity exec --bind {params.bind} {params.sif} sed 's/^ \+//g' {output.sexcheck} | singularity exec --bind {params.bind} {params.sif} sed 's/ \+/\t/g' > {output.sexcheck_tab}60        """61### Pull just common SNPs between two groups ###62rule common_snps:63    input:64        bed = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.pgen",65        bim = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.pvar",66        fam = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.psam",67    output:68        snps_data = output_dict["output_dir"] + "/common_snps/snps_data.tsv",69        snps_1000g = output_dict["output_dir"] + "/common_snps/snps_1000g.tsv",70        bed = output_dict["output_dir"] + "/common_snps/subset_data.pgen",71        bim = output_dict["output_dir"] + "/common_snps/subset_data.pvar",72        fam = output_dict["output_dir"] + "/common_snps/subset_data.psam",73        bed_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g.pgen",74        bim_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g.pvar",75        fam_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g.psam",76    resources:77        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["common_snps_memory"],78        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["common_snps_memory"]79    threads: plink_gender_ancestry_QC_dict["common_snps_threads"]80    params:81        bim_1000 = "/opt/1000G/all_phase3_filtered.pvar",82        bind = input_dict["bind_paths"],83        infile = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness",84        infile_1000g = "/opt/1000G/all_phase3_filtered",85        out = output_dict["output_dir"] + "/common_snps/subset_data",86        out_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g",87        sif = input_dict["singularity_image"]88    shell:89        """90        singularity exec --bind {params.bind} {params.sif} awk 'NR==FNR{{a[$1,$2,$4,$5];next}} ($1,$2,$4,$5) in a{{print $3}}' {input.bim} {params.bim_1000} > {output.snps_1000g}91        singularity exec --bind {params.bind} {params.sif} awk 'NR==FNR{{a[$1,$2,$4,$5];next}} ($1,$2,$4,$5) in a{{print $3}}' {params.bim_1000} {input.bim} > {output.snps_data}92        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile} --extract {output.snps_data} --make-pgen 'psam-cols='fid,parents,sex,phenos --out {params.out}93        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile_1000g} --extract {output.snps_1000g} --make-pgen --out {params.out_1000g}94        """95### Prune with --indep,96rule prune_1000g:97    input:98        bed_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g.pgen",99        bim_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g.pvar",100        fam_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g.psam",101        bim = output_dict["output_dir"] + "/common_snps/subset_data.pvar",102        bed = output_dict["output_dir"] + "/common_snps/subset_data.pgen",103        fam = output_dict["output_dir"] + "/common_snps/subset_data.psam",104    output:105        prune_out_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g.prune.out",106        prune_out = output_dict["output_dir"] + "/common_snps/subset_data.prune.out",107        bed_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g.pgen",108        bim_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g.pvar",109        fam_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g.psam",110        bed = output_dict["output_dir"] + "/common_snps/subset_pruned_data.pgen",111        bim = output_dict["output_dir"] + "/common_snps/subset_pruned_data.pvar",112        bim_temp = output_dict["output_dir"] + "/common_snps/subset_pruned_data_temp.pvar",113        bim_old = output_dict["output_dir"] + "/common_snps/subset_pruned_data_original.pvar",114        fam = output_dict["output_dir"] + "/common_snps/subset_pruned_data.psam",115        data_1000g_key = output_dict["output_dir"] + "/common_snps/subset_pruned_data_1000g_key.txt",116        SNPs2keep = output_dict["output_dir"] + "/common_snps/SNPs2keep.txt"117    resources:118        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["prune_1000g_memory"],119        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["prune_1000g_memory"]120    threads: plink_gender_ancestry_QC_dict["prune_1000g_threads"]121    params:122        bind = input_dict["bind_paths"],123        sif = input_dict["singularity_image"],124        out_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g",125        infile_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g",126        infile = output_dict["output_dir"] + "/common_snps/subset_data",127        out = output_dict["output_dir"] + "/common_snps/subset_pruned_data"128    shell:129        """130        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile_1000g} \131            --indep-pairwise 50 5 0.5 \132            --out {params.out_1000g}133        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile_1000g} --extract {output.prune_out_1000g} --make-pgen --out {params.out_1000g}134        if [[ $(grep "##" {input.bim} | wc -l) > 0 ]]135        then136            singularity exec --bind {params.bind} {params.sif} grep "##" {input.bim} > {output.data_1000g_key}137        fi138        singularity exec --bind {params.bind} {params.sif} awk -F"\\t" 'BEGIN{{OFS=FS = "\\t"}} NR==FNR{{a[$1 FS $2 FS $4 FS $5] = $0; next}} {{ind = $1 FS $2 FS $4 FS $5}} ind in a {{print a[ind], $3}}' {output.bim_1000g} {input.bim} | singularity exec --bind {params.bind} {params.sif} grep -v "##" >> {output.data_1000g_key}139        singularity exec --bind {params.bind} {params.sif} grep -v "##" {output.data_1000g_key} | singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}{{print $NF}}' > {output.prune_out}140        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile} --extract {output.prune_out} --make-pgen 'psam-cols='fid,parents,sex,phenos --out {params.out}141        singularity exec --bind {params.bind} {params.sif} cp {output.bim} {output.bim_old}142        singularity exec --bind {params.bind} {params.sif} grep -v "#" {output.bim_old} | singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}{{print($3)}}' > {output.SNPs2keep}143        singularity exec --bind {params.bind} {params.sif} grep "#CHROM" {output.data_1000g_key} > {output.bim}144        singularity exec --bind {params.bind} {params.sif} grep -Ff {output.SNPs2keep} {output.data_1000g_key} >> {output.bim}145        singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}NF{{NF-=1}};1' < {output.bim} > {output.bim_temp}146        singularity exec --bind {params.bind} {params.sif} grep "##" {output.bim_1000g} > {output.bim}147        singularity exec --bind {params.bind} {params.sif} cat {output.bim_temp} >> {output.bim}148        """149        150rule final_pruning: ### put in contingency for duplicated snps - remove from both 1000G and your dataset151    input:152        bed = output_dict["output_dir"] + "/common_snps/subset_pruned_data.pgen",153        bim = output_dict["output_dir"] + "/common_snps/subset_pruned_data.pvar",154        fam = output_dict["output_dir"] + "/common_snps/subset_pruned_data.psam",155    output:156        bed = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data.pgen",157        bim = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data.pvar",158        fam = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data.psam",159    resources:160        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["prune_1000g_memory"],161        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["prune_1000g_memory"]162    threads: plink_gender_ancestry_QC_dict["prune_1000g_threads"]163    params:164        bind = input_dict["bind_paths"],165        sif = input_dict["singularity_image"],166        infile = output_dict["output_dir"] + "/common_snps/subset_pruned_data",167        out = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data"168    shell:169        """170        singularity exec --bind {params.bind} {params.sif} plink2 --rm-dup 'force-first' -threads {threads} --pfile {params.infile} --make-pgen 'psam-cols='fid,parents,sex,phenos --out {params.out}171        """172### use PCA from plink for PCA and projection173rule pca_1000g:174    input:175        bed_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g.pgen",176        bim_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g.pvar",177        fam_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g.psam",178        bed = output_dict["output_dir"] + "/common_snps/subset_pruned_data.pgen" 179    output:180        out = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs.acount",181        eig_all = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs.eigenvec.allele",182        eig_vec = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs.eigenvec",183        eig = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs.eigenval",184    resources:185        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["pca_1000g_memory"],186        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["pca_1000g_memory"]187    threads: plink_gender_ancestry_QC_dict["pca_1000g_threads"]188    params:189        bind = input_dict["bind_paths"],190        sif = input_dict["singularity_image"],191        infile = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g",192        out = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs"193    shell:194        """195        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile} \196            --freq counts \197            --pca allele-wts \198            --out {params.out}199        """200### use plink pca results to plot with R ###201rule pca_project:202    input:203        bed = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data.pgen",204        bim = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data.pvar",205        fam = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data.psam",206        frq = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs.acount",207        scores = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs.eigenvec.allele"208    output:209        projected_scores = output_dict["output_dir"] + "/pca_projection/final_subset_pruned_data_pcs.sscore",210        projected_1000g_scores = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs_projected.sscore"211    resources:212        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["pca_project_memory"],213        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["pca_project_memory"]214    threads: plink_gender_ancestry_QC_dict["pca_project_threads"]215    params:216        bind = input_dict["bind_paths"],217        sif = input_dict["singularity_image"],218        infile = output_dict["output_dir"] + "/common_snps/final_subset_pruned_data",219        infile_1000g = output_dict["output_dir"] + "/common_snps/subset_pruned_1000g",220        out = output_dict["output_dir"] + "/pca_projection/final_subset_pruned_data_pcs",221        out_1000g = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs_projected"222    shell:223        """224        export OMP_NUM_THREADS={threads}225        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile} \226            --read-freq {input.frq} \227            --score {input.scores} 2 5 header-read no-mean-imputation \228                    variance-standardize \229            --score-col-nums 6-15 \230            --out {params.out}231        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile_1000g} \232            --read-freq {input.frq} \233            --score {input.scores} 2 5 header-read no-mean-imputation \234                    variance-standardize \235            --score-col-nums 6-15 \236            --out {params.out_1000g}237       """238rule pca_projection_assign:239    input:240        projected_scores = output_dict["output_dir"] + "/pca_projection/final_subset_pruned_data_pcs.sscore",241        projected_1000g_scores = output_dict["output_dir"] + "/pca_projection/subset_pruned_1000g_pcs_projected.sscore",242        fam_1000g = output_dict["output_dir"] + "/common_snps/subset_1000g.psam",243        psam = psam,244        sexcheck = output_dict["output_dir"] + "/check_sex/check_sex.sexcheck.tsv",245    output:246        sexcheck = output_dict["output_dir"] + "/pca_sex_checks/check_sex_update_remove.tsv",247        anc_check = output_dict["output_dir"] + "/pca_sex_checks/ancestry_update_remove.tsv",248        anc_fig = report(output_dict["output_dir"] + "/pca_sex_checks/Ancestry_PCAs.png", category = "Ancestry", caption = "../report_captions/ancestry_pca.rst")249    resources:250        mem_per_thread_gb=lambda wildcards, attempt: attempt * 10,251        disk_per_thread_gb=lambda wildcards, attempt: attempt * 10252    threads: 2253    params:254        variables = output_dict["output_dir"] + "/pca_sex_checks/variables.tsv",255        bind = input_dict["bind_paths"],256        sif = input_dict["singularity_image"],257        outdir = output_dict["output_dir"] + "/pca_sex_checks/",258        script = "/opt/WG1-pipeline-QC/Imputation/scripts/PCA_Projection_Plotting.R"259    shell:260        """261        singularity exec --bind {params.bind} {params.sif} echo {params.outdir} > {params.variables}262        singularity exec --bind {params.bind} {params.sif} echo {input.projected_scores} >> {params.variables}263        singularity exec --bind {params.bind} {params.sif} echo {input.projected_1000g_scores} >> {params.variables}264        singularity exec --bind {params.bind} {params.sif} echo {input.fam_1000g} >> {params.variables}265        singularity exec --bind {params.bind} {params.sif} echo {input.psam} >> {params.variables}266        singularity exec --bind {params.bind} {params.sif} echo {input.sexcheck} >> {params.variables}267        singularity exec --bind {params.bind} {params.sif} Rscript {params.script} {params.variables}268        """269rule summary_ancestry_sex:270    input:271        sexcheck = output_dict["output_dir"] + "/check_sex/check_sex.sexcheck.tsv",272        sexcheck_tsv = output_dict["output_dir"] + "/pca_sex_checks/check_sex_update_remove.tsv",273        fam = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.psam",274        anc_check = output_dict["output_dir"] + "/pca_sex_checks/ancestry_update_remove.tsv"275    output:276        report(output_dict["output_dir"] + "/metrics/sex_summary.png", category = "Ancestry and Sex Summary", caption = "../report_captions/sex_summary.rst"),277        report(output_dict["output_dir"] + "/metrics/ancestry_summary.png", category = "Ancestry and Sex Summary", caption = "../report_captions/ancestry_summary.rst")278    resources:279        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["summary_ancestry_sex_memory"],280        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["summary_ancestry_sex_memory"]281    threads: plink_gender_ancestry_QC_dict["summary_ancestry_sex_threads"]282    params:283        bind = input_dict["bind_paths"],284        sif = input_dict["singularity_image"],285        outdir = output_dict["output_dir"] + "/metrics/",286        basedir = output_dict["output_dir"],287        script = "/opt/WG1-pipeline-QC/Imputation/scripts/sex_ancestry_summaries.R"288    shell:289        """290        singularity exec --bind {params.bind} {params.sif} Rscript {params.script} {params.basedir} {params.outdir}291        """292rule separate_indivs:293    input:294        sexcheck = output_dict["output_dir"] + "/pca_sex_checks/check_sex_update_remove.tsv",295        anc_check = output_dict["output_dir"] + "/pca_sex_checks/ancestry_update_remove.tsv"296    output:297        update_sex = output_dict["output_dir"] + "/separate_indivs/sex_update_indivs.tsv",298        remove_indiv = output_dict["output_dir"] + "/separate_indivs/remove_indivs.tsv",299        remove_indiv_temp = output_dict["output_dir"] + "/separate_indivs/remove_indivs_temp.tsv",300    resources:301        mem_per_thread_gb=lambda wildcards, attempt: attempt * 5,302        disk_per_thread_gb=lambda wildcards, attempt: attempt * 5303    threads: 1304    params:305        bind = input_dict["bind_paths"],306        sif = input_dict["singularity_image"],307    shell:308        """309        singularity exec --bind {params.bind} {params.sif} grep "UPDATE" {input.sexcheck} | singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}{{print($1,$2,$4)}}' | singularity exec --bind {params.bind} {params.sif} sed 's/SNPSEX/SEX/g' > {output.update_sex}310        singularity exec --bind {params.bind} {params.sif} grep "REMOVE" {input.sexcheck} | singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}{{print($1,$2)}}'> {output.remove_indiv_temp}311        singularity exec --bind {params.bind} {params.sif} grep "REMOVE" {input.anc_check} | singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}{{print($1,$2)}}' >> {output.remove_indiv_temp}312        singularity exec --bind {params.bind} {params.sif} sort -u {output.remove_indiv_temp} > {output.remove_indiv}313        """314rule update_sex_ancestry:315    input:316        bim = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness.pgen",317        psam = psam,318        update_sex = output_dict["output_dir"] + "/separate_indivs/sex_update_indivs.tsv",319        remove_indiv = output_dict["output_dir"] + "/separate_indivs/remove_indivs.tsv",320    output:321        bed = output_dict["output_dir"] + "/update_sex_ancestry/update_sex.pgen",322        bim = output_dict["output_dir"] + "/update_sex_ancestry/update_sex.pvar",323        psam = output_dict["output_dir"] + "/update_sex_ancestry/update_sex.psam",324    resources:325        mem_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["update_sex_memory"],326        disk_per_thread_gb=lambda wildcards, attempt: attempt * plink_gender_ancestry_QC_dict["update_sex_memory"]327    threads: plink_gender_ancestry_QC_dict["update_sex_threads"]328    params:329        anc_updated_psam = output_dict["output_dir"] + "/pca_sex_checks/updated_psam.psam",330        infile = output_dict["output_dir"] + "/indiv_missingness/indiv_missingness",331        psam_temp = output_dict["output_dir"] + "/update_sex_ancestry/temp/indiv_missingness.psam_temp",332        tdir = output_dict["output_dir"] + "/update_sex_ancestry/temp/",333        bind = input_dict["bind_paths"],334        out = output_dict["output_dir"] + "/update_sex_ancestry/update_sex",335        sif = input_dict["singularity_image"]336    shell:337        """338        singularity exec --bind {params.bind} {params.sif} mkdir -p {params.tdir}339        singularity exec --bind {params.bind} {params.sif} cp {params.infile}* {params.tdir}340        singularity exec --bind {params.bind} {params.sif} cp {params.anc_updated_psam} {params.tdir}/indiv_missingness.psam 341        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.tdir}/indiv_missingness --update-sex {input.update_sex} --remove {input.remove_indiv} --make-pgen 'psam-cols='fid,parents,sex,phenos --out {params.out}342        """343rule subset_ancestry:344    input:345        psam = output_dict["output_dir"] + "/update_sex_ancestry/update_sex.psam"346    output:347        keep = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_individuals.psam",348        pgen = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset.pgen",349        psam = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset.psam",350        pvar = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset.pvar"351    resources: 352        mem_per_thread_gb = lambda wildcards, attempt: attempt * 1,353        disk_per_thread_gb = lambda wildcards, attempt: attempt * 1354    threads: 1355    params:356        bind = input_dict["bind_paths"],357        sif = input_dict["singularity_image"],358        infile = output_dict["output_dir"] + "/update_sex_ancestry/update_sex",359        out = output_dict["output_dir"] + "/subset_ancestry/{ancestry}_subset"360    shell:361        """362        singularity exec --bind {params.bind} {params.sif} grep {wildcards.ancestry} {input.psam} > {output.keep}363        singularity exec --bind {params.bind} {params.sif} plink2 --threads {threads} --pfile {params.infile} --keep {output.keep} --max-alleles 2 --make-pgen 'psam-cols='fid,parents,sex,phenos --out {params.out}...

Snakefile

Source:Snakefile

1import os2import sys3import argparse4import glob5from pathlib import Path6import re7if os.path.exists('config.yaml'):8	configfile: 'config.yaml'9# print function for debugging in snakemake10def eprint(*args, **kwargs):11	print(*args, file=sys.stderr, **kwargs)12input_dir=config['input_dir']13input_sample=config['input_sample']14core_genome=config['core_genome']15output_dir=config['output_dir']16include_to_final=config['include']17SNP_distance=config['SNP_distance']18prefix=config['prefix']19# check if files are fastq.gz:20def check_fastq_end():21	fastqs = glob.glob(input_dir+'/'+input_sample+"*R1*"); fastqs += glob.glob(input_dir+'/'+input_sample+"*R2*")22	for fastq in fastqs:23		if not fastq.endswith('fastq.gz') and not fastq.endswith('fq.gz'):24			raise Exception("ERROR Input files must be fastq.gz or fq.gz !")25		return26check_fastq_end()27READS={}28READS['R1'] = glob.glob(input_dir+'/'+input_sample+"*R1*")[0]29READS['R2'] = glob.glob(input_dir+'/'+input_sample+"*R2*")[0]30# check if the file is already present in the matrix. Authomatically set include to False if the file is already in the matrix.31def check_if_exists_in_matrix():32	myfile_dist=Path(output_dir+'/output_files/complete_clonetype_distance_matrix.txt')33        if myfile_dist.is_file():34		with open(output_dir+'/output_files/complete_clonetype_distance_matrix.txt') as f:35			names = [line.split('\t')[0] for line in f][1:]36		trimmed_names = [name.split('::')[1] for name in names]37		if input_sample in trimmed_names:38			if include_to_final is True:39				config['include']=False40				eprint("The file already exists in the matrix. Parameter \"Include\" is set to False")41check_if_exists_in_matrix()42def number_of_existing_samples():43	myfile_aln=Path(output_dir+'/output_files/complete_clonetype_sorted_alignment.fa')44	if myfile_aln.is_file():45		sample_no=int(sum(1 for line in open(output_dir+'/output_files/complete_clonetype_sorted_alignment.fa') if line.rstrip())/2)46	else:47		sample_no=048	return(sample_no)49sample_no=number_of_existing_samples()50# exclude all the names which are non-numeric51def follows_the_pattern(name):52	if(re.compile("[0-9][0-9][0-9]").match(name)):53		return True54	else:55		return False56def new_clonetype():57	myfile_dist=Path(output_dir+'/output_files/complete_clonetype_distance_matrix.txt')58	if myfile_dist.is_file():59		with open(output_dir+'/output_files/complete_clonetype_distance_matrix.txt') as f:60			names = [line.split('\t')[0] for line in f]61		num = [name.split('::')[0][-3:] for name in names]62		numbers=int(max(filter(follows_the_pattern, num)))+163	elif sample_no==1:64		numbers=265	else:66		numbers=167	return("{:03d}".format(numbers))68new_ct=new_clonetype()69now_ct=float(new_ct)-170eprint("Previously analyzed and added sample number:",sample_no)71eprint("Number of already existing clone types in the data set is:", int(now_ct))72rule all:73	input:74		vcf_gz=expand("{output_dir}/sample_alignments/{sample}/{sample}.vcf.gz", sample=config['input_sample'], output_dir=config['output_dir']),75		aligned=expand("{output_dir}/sample_alignments/{sample}/{sample}.aligned.fa", sample=config['input_sample'], output_dir=config['output_dir']),76		stats=expand("{output_dir}/sample_alignments/{sample}/alignment_statistics.txt", sample=config['input_sample'], output_dir=config['output_dir']),77		snp_dist=expand("{output_dir}/sample_alignments/{sample}/{sample}_clonetype_snp_distances.txt", output_dir=config['output_dir'], sample=config['input_sample']) if sample_no>=1 else [],78		initial_alignment=expand("{output_dir}/output_files/complete_clonetype_sorted_alignment.fa", output_dir=config['output_dir']) if sample_no==0 else [],79		clonetype_stats=expand("{output_dir}/sample_alignments/{sample}/{sample}_clonetype_summary.txt", output_dir=config['output_dir'], sample=config['input_sample']) if sample_no>=1 else []80	message:81		"Pipeline complete"82# Run snippy on the input sample using the core reference genome83rule run_snippy:84	input:85		R1=READS['R1'],86		R2=READS['R2']	87	output:88		vcf_gz=expand("{output_dir}/sample_alignments/{sample}/{sample}.vcf.gz", sample=config['input_sample'], output_dir=config['output_dir']),89		aligned=expand("{output_dir}/sample_alignments/{sample}/{sample}.aligned.fa", sample=config['input_sample'], output_dir=config['output_dir']),90		ref=temp(expand("{output_dir}/sample_alignments/{sample}/ref.fa", sample=config['input_sample'], output_dir=config['output_dir'])),91		ref_fai=temp(expand("{output_dir}/sample_alignments/{sample}/ref.fa.fai", sample=config['input_sample'], output_dir=config['output_dir'])),92		bam=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.bam", sample=config['input_sample'], output_dir=config['output_dir'])),93		bam_bai=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.bam.bai", sample=config['input_sample'], output_dir=config['output_dir'])),94		raw_vcf=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.raw.vcf", sample=config['input_sample'], output_dir=config['output_dir'])),95		filt_vcf=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.filt.vcf", sample=config['input_sample'], output_dir=config['output_dir'])),96		vcf=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.vcf", sample=config['input_sample'], output_dir=config['output_dir'])),97		tab=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.tab", sample=config['input_sample'], output_dir=config['output_dir'])),98		subs_vcf=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.subs.vcf", sample=config['input_sample'], output_dir=config['output_dir'])),99		consensus_fa=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.consensus.fa", sample=config['input_sample'], output_dir=config['output_dir'])),100		consensus_subs_fa=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.consensus.subs.fa", sample=config['input_sample'], output_dir=config['output_dir'])),101		log_file=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.log", sample=config['input_sample'], output_dir=config['output_dir'])),102		bed=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.bed", sample=config['input_sample'], output_dir=config['output_dir'])),103		gff=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.gff", sample=config['input_sample'], output_dir=config['output_dir'])),104		csv=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.csv", sample=config['input_sample'], output_dir=config['output_dir'])),105		html=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.html", sample=config['input_sample'], output_dir=config['output_dir'])),106		txt=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.txt", sample=config['input_sample'], output_dir=config['output_dir']))107		108	params:109		outdir=config['output_dir'],110		ref=config['core_genome'],111		prefix=config['input_sample'],112		cpus=10,113		mincov=10114	message:115		"Running snippy variant calling for {params.prefix}."116	log:117		expand("{output_dir}/logs/snippy_{sample}.log", output_dir=config["output_dir"], sample=config['input_sample'])118	shell:119		"""120		module unload anaconda3/4.0.0121		module load anaconda2/4.0.0122		module load tbl2asn/20190117123		module load parallel/20190122124		module load bwa/0.7.15125		module load samtools/1.9126		module load java/1.8.0127		module load jre/1.8.0128		module load perl/5.24.0129		module load freebayes/1.1.0-50-g61527c5130		module load vcflib/1.0.0-rc2131		module load vcftools/0.1.16132		module load snpeff/4.3r133		module load prokka/1.12134		module load minimap2/2.6135		module load seqtk/1.0-r82-dirty136		module load snp-sites/2.4.0137		module load emboss/6.6.0138		module load bcftools/1.9139		module load snippy/4.4.0140		module load vt/0.5772141		(snippy --outdir {params.outdir}/sample_alignments/{params.prefix} --ref {params.ref} --R1 {input.R1} --R2 {input.R2} --prefix {params.prefix} --cpus {params.cpus}  --force --mincov {params.mincov}) 2> {log}142		# how to add to a previous SNP distance? cp - if include is No, add if include is Yes?143		"""144def do_QC(fasta_file, output_file, log_file):145	with open(fasta_file, "r") as f:146		sequence = "".join(line.strip() for line in f if line[:1]!=">")147		seq_len = len(sequence)148		missing_len = sequence.count("N")+sequence.count("-")149		cons_positions = seq_len - missing_len150		missing_percent = (missing_len*100)/seq_len151		present_percent = 100 - missing_percent152	f.closed153	if missing_percent >20:154		with open(log_file, "w") as logf:155			logf.write("Core genome consists of {total} positions.\n\156In total {considered} positions were covered by not less than 10 reads.\n\157{covered}% of positions were covered by not less than 10 reads.\n".format(total=seq_len, considered=cons_positions, covered=round(present_percent, 2)))158		raise Exception("ERROR: The sequence alignment is less than 80% of the reference sequence. Analysis can't be continued because of low coverage.")159	else:160		print("Sequence alignment covers 80% or more of the reference sequence")161		with open(output_file, "w") as outf:162			outf.write("Core genome consists of {total} positions.\n\163In total {considered} positions were covered by not less than 10 reads.\n\164{covered}% of postions were covered by not less than 10 reads.\n".format(total=seq_len, considered=cons_positions, covered=round(present_percent, 2)))165			166		167# Check if the alignment covers >=80% of the reference core genome168rule do_QC:169	input:170		expand("{output_dir}/sample_alignments/{sample}/{sample}.aligned.fa", sample=config['input_sample'], output_dir=config['output_dir'])171	output:172		expand("{output_dir}/sample_alignments/{sample}/alignment_statistics.txt", sample=config['input_sample'], output_dir=config['output_dir'])173	log:174		expand("{output_dir}/sample_alignments/{sample}/unsuccessful_alignment_statistics.txt", sample=config['input_sample'], output_dir=config['output_dir'])175	message:176		"Performing quality check of the alignment coverage."177	run:178		do_QC(input[0], output[0], log[0])179if sample_no >= 2:180# SNP distance analysis on the provided samples181	rule snp_dists:182		input:183			aligned_file=expand("{output_dir}/sample_alignments/{sample}/{sample}.aligned.fa", sample=config['input_sample'], output_dir=config['output_dir']),184			initial_alignment=expand("{output_dir}/output_files/complete_clonetype_sorted_alignment.fa", output_dir=config['output_dir']),185			alignment_statistics=expand("{output_dir}/sample_alignments/{sample}/alignment_statistics.txt", sample=config['input_sample'], output_dir=config['output_dir'])186		output:187			consensus_sample=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.consensus.fa", sample=config['input_sample'], output_dir=config['output_dir'])),188			snp_dist=expand("{output_dir}/sample_alignments/{sample}/{sample}_clonetype_snp_distances.txt", output_dir=config['output_dir'], sample=config['input_sample']),189			temp_names=temp(expand("{output_dir}/output_files/temporary_names_snp_dist.txt", output_dir=config['output_dir'])),190			temp_dist=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}_temp_distances.txt", sample=config['input_sample'], output_dir=config['output_dir'])),191			temp_fasta=temp(expand("{output_dir}/sample_alignments/{sample}/temp_fasta.fa", output_dir=config['output_dir'], sample=config['input_sample'])),192		params:193			initial_distance=expand("{output_dir}/output_files/complete_clonetype_distance_matrix.txt", output_dir=config['output_dir']) if include_to_final == True else [],194			temp_consensus=temp(expand("{output_dir}/output_files/temp_complete_clonetype_sorted_alignment.fa", output_dir=config['output_dir'])),195			sample=config['input_sample'],196			incl=config['include']197		message:198			"Performing SNP distance analysis on the {params.sample}."199		shell:200			"""201			module load pigz/2.3.4202			module load seqkit/0.7.1	203			# creating a sorted fasta file with all the genes merged in one sequence204	205			seqkit sort --id-regexp "(.+)" {input.aligned_file} | grep -v "^>" | awk \'!/^>/ {{ printf "%s", $0; n = "\\n" }} /^>/ {{ print n $0; n = "" }} END {{ printf "%s", n }}\' |  sed "1s/^/>{params.sample}\\n/" > {output.consensus_sample}206			# performing snp-dist for each sample pair (new sample vs every older sample)207		208			cat {input.initial_alignment} | nl | grep ">" > {output.temp_names}	209			echo {params.sample} > {output.temp_dist}210		211			while read line name212			do213				# adding a 1 to the line number so both name and sequence would be included214				new_line=`echo "$line"+1 | bc`215				seq=`head -n $new_line {input.initial_alignment} | tail -2`216				new_seq=`cat {output.consensus_sample}`217				echo "$seq" > {output.temp_fasta}218				echo "$new_seq" >> {output.temp_fasta}219				dist=`snp-dists -q -b {output.temp_fasta} | tail -1  | cut -f 2`220				echo "$dist"221			done < {output.temp_names} >> {output.temp_dist}222	223			# merging the initial distance table with the new results224			paste {params.initial_distance} {output.temp_dist} > {output.snp_dist}	225		226			hline=`cat {output.temp_dist} | tr "\\n" "\\t" | sed "s/$/0\\n/"`227			echo "$hline" >> {output.snp_dist}	228			229		230			# if include is true output snps distance file and initial alignment file should be updated with the new file. Filename should be changed in the next rule.231			if [[ {params.incl} == "True" ]]232			then233				cat {input.initial_alignment} {output.consensus_sample} > {params.temp_consensus}234				mv {params.temp_consensus} {input.initial_alignment}235			236				cp {output.snp_dist} {params.initial_distance}237			fi238			"""239if sample_no == 1:240	rule snp_dists:241		input:242			aligned_file=expand("{output_dir}/sample_alignments/{sample}/{sample}.aligned.fa", sample=config['input_sample'], output_dir=config['output_dir']),243			initial_alignment=expand("{output_dir}/output_files/complete_clonetype_sorted_alignment.fa", output_dir=config['output_dir']),244			alignment_statistics=expand("{output_dir}/sample_alignments/{sample}/alignment_statistics.txt", sample=config['input_sample'], output_dir=config['output_dir'])245		output:246			consensus_sample=temp(expand("{output_dir}/sample_alignments/{sample}/{sample}.consensus.fa", sample=config['input_sample'], output_dir=config['output_dir'])),247			snp_dist=expand("{output_dir}/sample_alignments/{sample}/{sample}_clonetype_snp_distances.txt", output_dir=config['output_dir'], sample=config['input_sample']),248			temp_fasta=temp(expand("{output_dir}/sample_alignments/{sample}/temp_fasta.fa", output_dir=config['output_dir'], sample=config['input_sample'])),249			initial_distance=expand("{output_dir}/output_files/complete_clonetype_distance_matrix.txt", output_dir=config['output_dir'])250		params:251			temp_consensus=temp(expand("{output_dir}/output_files/temp_complete_clonetype_sorted_alignment.fa", output_dir=config['output_dir'])),252			sample=config['input_sample'],253			incl=config['include']254		message:255			"Performing SNP distance analysis on the {params.sample}."256		shell:257			"""258			module load pigz/2.3.4259			module load seqkit/0.7.1260			# creating a sorted fasta file with all the genes merged in one sequence261			seqkit sort --id-regexp "(.+)" {input.aligned_file} | grep -v "^>" | awk \'!/^>/ {{ printf "%s", $0; n = "\\n" }} /^>/ {{ print n $0; n = "" }} END {{ printf "%s", n }}\' |  sed "1s/^/>{params.sample}\\n/" > {output.consensus_sample}262			# performing snp-dists for the only two samples which are available263			cat {input.initial_alignment} {output.consensus_sample} > {output.temp_fasta}264			snp-dists -q -b {output.temp_fasta} > {output.snp_dist}265		266			# output snps distance file and initial alignment file should be updated with the new file. Filename should be changed in the next rule.267			268			cat {input.initial_alignment} {output.consensus_sample} > {params.temp_consensus}269			mv {params.temp_consensus} {input.initial_alignment}270			cp {output.snp_dist} {output.initial_distance}271			272			"""273# If there is only one alignment, the alignment should be added to the complete_alignment if include is YES file and no further action should be done.274rule create_complete_aligment:275	input:276		aligned_file=expand("{output_dir}/sample_alignments/{sample}/{sample}.aligned.fa", sample=config['input_sample'], output_dir=config['output_dir'])277	output:278		initial_alignment=expand("{output_dir}/output_files/complete_clonetype_sorted_alignment.fa", output_dir=config['output_dir']) if sample_no<1 else []279	params:280		prefix=config['prefix'],281		sample=config['input_sample']282	message:283		"Adding the sample to the multiple sequence FASTA file"284	shell:285		"""286		module load pigz/2.3.4287		module load seqkit/0.7.1288		# creating a sorted fasta file with all the genes merged in one sequence289		seqkit sort --id-regexp "(.+)" {input.aligned_file} |  grep -v "^>" | awk \'!/^>/ {{ printf "%s", $0; n = "\\n" }} /^>/ {{ print n $0; n = "" }} END {{ printf "%s", n }}\' |  sed "1s/^/>{params.prefix}001::{params.sample}\\n/" > {output.initial_alignment}290		"""291# Estimation of the closest clone types. If the SNP difference is <5000 SNPs, the isolate is given a clone type. Otherwise, it is considered a new clone type.292rule estimate_clonetype:293	input:294		snp_dist=expand("{output_dir}/sample_alignments/{sample}/{sample}_clonetype_snp_distances.txt", output_dir=config['output_dir'], sample=config['input_sample']),295		initial_alignment=expand("{output_dir}/output_files/complete_clonetype_sorted_alignment.fa", output_dir=config['output_dir']),296		initial_distance=expand("{output_dir}/output_files/complete_clonetype_distance_matrix.txt", output_dir=config['output_dir'])297	output:298		stats=expand("{output_dir}/sample_alignments/{sample}/{sample}_clonetype_summary.txt", output_dir=config['output_dir'], sample=config['input_sample']),299		temp_clonetype_list=temp(expand("{output_dir}/output_files/temp_{sample}_clonetype_list.txt", output_dir=config['output_dir'], sample=config['input_sample']))300	params:301		prefix=config['prefix'],302		distance=config['SNP_distance'],303		incl=config['include'],304		sample=config['input_sample'],305		new_clonetype=new_ct306	message:307		"Predicting the clone type for the input sample"308	shell:309		"""310		module load datamash/1.4311		close_clonetypes=`cat {input.snp_dist} | tail -1  | cut -f 2- | datamash transpose | head -n -1 | nl | awk '$2<{params.distance} {{print $1}}'`312		if [[ ! -z "$close_clonetypes" ]]313		then314			while read line315			do316				new_num=`echo "$line" +1 | bc`317				head -1 {input.initial_distance} | cut -f "$new_num"  | sed 's/::.*//'318			done <<< "$close_clonetypes" >> {output.temp_clonetype_list}319			320			clonetype_number=`cat {output.temp_clonetype_list} | sort | uniq -c | sort -k1,1n`321	322			line_number=`echo "$clonetype_number" | wc -l`323	324		else325			touch {output.temp_clonetype_list}326			line_number=0327		fi328	329		# if only one clone type is predicted:	330		if [[ "$line_number" == 1  ]]331		then332			number=`echo "$clonetype_number" | awk '{{print $1}}'`333			clonetype=`echo "$clonetype_number" | awk '{{print $2}}'`334			total_number=`cat {input.snp_dist} | cut -f 1 | grep -w "$clonetype" | wc -l`335			336			echo "The {params.sample} sample has less than {params.distance} SNP distance to the "$clonetype" clone type.337In total "$number" out of "$total_number" samples with this clone type fall below the SNP distance threshold." > {output.stats}338		elif [[ "$line_number" > 1 ]]339		then340			echo "WARNING! More than one clone type has smaller SNP distance than {params.distance} to the {params.sample}.341You might want to reconsider SNP distance threshold. If the sample is set to be included in the final SNP distance matrix, the most often occuring clone type will be used. It might cause problems in the future analysis. \The following clone types are reported to be close to the {params.sample} sample:" > {output.stats}342			while read clonetype_line343			do344				number=`echo "$clonetype_line" | awk '{{print $1}}'`345				clonetype=`echo "$clonetype_line" | awk '{{print $2}}'`346				total_number=`cat {input.snp_dist} | cut -f 1 | grep -w "$clonetype" | wc -l`347				echo "Clonetype "$clonetype" in "$number" out of "$total_number" samples with this clonetype which fall below the SNP distance threshold." >> {output.stats}348		349			done <<< "$clonetype_number"350	351		elif [[ "$line_number" == 0 ]]352		then353			echo "No already existing clone types are closer than the {params.distance} SNP distance threshold.354New clone type assigned: {params.new_clonetype}" > {output.stats}355			clonetype={params.prefix}{params.new_clonetype}356		fi357		# if include is true change the name of complete snp distance and sorted alignment files to the name of the assigned clone type358		if [[ {params.incl} == "True" ]]359		then360			sed -i "s/^>{params.sample}/>\"$clonetype\"::{params.sample}/" {input.initial_alignment}361			sed -i "s/{params.sample}/\"$clonetype\"::{params.sample}/" {input.initial_distance}362		fi363		"""...

Snakefile_CombineResults.smk

Source:Snakefile_CombineResults.smk

1#!/usr/bin/env python2import os3import pandas as pd4from glob import glob5#################################6######## COMBINE RESULTS ########7#################################8if os.path.exists(output_dict["output_dir"] + "/manual_selections/scrublet/scrublet_percentile_manual_selection.tsv"):9    scrublet_selection = pd.read_csv(output_dict["output_dir"] + "/manual_selections/scrublet/scrublet_percentile_manual_selection.tsv", sep = "\t")10rule join_results:11    input:12        demuxlet = output_dict["output_dir"] + "/{pool}/CombinedResults/demuxlet_results.txt",13        souporcell = output_dict["output_dir"] + "/{pool}/CombinedResults/souporcell_results.txt",14        scrublet = lambda wildcards: expand(output_dict["output_dir"] + "/{pool}/CombinedResults/{pctl}_scrublet_results.txt", zip, pool = wildcards.pool, pctl = scrublet_selection.scrublet_Percentile[scrublet_selection.Pool == wildcards.pool]),15        scds = output_dict["output_dir"] + "/{pool}/CombinedResults/scds_results.txt",16        DoubletDetection = output_dict["output_dir"] + "/{pool}/CombinedResults/DoubletDetection_results.txt"17    output:18        output_dict["output_dir"] + "/{pool}/CombinedResults/CombinedDropletAssignments.tsv"19    resources:20        mem_per_thread_gb=5,21        disk_per_thread_gb=522    threads: 123    params:24        sif = input_dict["singularity_image"],25        bind = bind_path26    log: output_dict["output_dir"] + "/logs/join_results.{pool}.log"27    shell:28        """29        join -a1 -a2 -1 1 -2 1 -t "\t" -e"NA" -o "0,1.2,1.3,1.4,1.5,1.6,1.7,2.2,2.3,2.4,2.5" {input.demuxlet} {input.souporcell} | awk 'NR<2{{print $0;next}}{{print $0| "sort -k1"}}' | \30            join -a1 -a2 -1 1 -2 1 -t "\t" -e"NA" -o "0,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,1.10,1.11,2.2,2.3" - {input.scrublet} | awk 'NR<2{{print $0;next}}{{print $0| "sort -k1"}}' | \31            join -a1 -a2 -1 1 -2 1 -t "\t" -e"NA" -o "0,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,1.10,1.11,1.12,1.13,2.2,2.3" - {input.scds} | awk 'NR<2{{print $0;next}}{{print $0| "sort -k1"}}' | \32            join -a1 -a2 -1 1 -2 1 -t "\t" -e"NA" -o "0,1.2,1.3,1.4,1.5,1.6,1.7,1.8,1.9,1.10,1.11,1.12,1.13,1.14,1.15,2.2" - {input.DoubletDetection} > {output}33        """34#####################################################################35############ SCRIPT FOR CALLING FINAL BARCODE ASSIGNMENT ############36#####################################################################37rule final_assignments:38    input:39        assignments = output_dict["output_dir"] + "/{pool}/CombinedResults/CombinedDropletAssignments_w_genotypeIDs.tsv"40    output:41        figure = report(output_dict["output_dir"] + "/{pool}/CombinedResults/DropletType_Assignment_BarPlot.png", category = "Number Individuals Summary", caption =  "../report_captions/final_assignments.rst"),42        table = output_dict["output_dir"] + "/{pool}/CombinedResults/Final_Assignments_demultiplexing_doublets.txt",43        variables = output_dict["output_dir"] + "/{pool}/CombinedResults/variables.txt"44    resources:45        mem_per_thread_gb = lambda wildcards, attempt: attempt * CombineResults_dict["FinalAssignments_memory"],46        disk_per_thread_gb = lambda wildcards, attempt: attempt * CombineResults_dict["FinalAssignments_memory"]47    threads: CombineResults_dict["FinalAssignments_threads"]48    params:49        sif = input_dict["singularity_image"],50        bind = bind_path,51        out = output_dict["output_dir"],52        script = "/opt/WG1-pipeline-QC/Demultiplexing/scripts/FinalBarcodeAssignments.R"53    log: output_dict["output_dir"] + "/logs/final_assignments.{pool}.log"54    shell:55        """56        singularity exec --bind {params.bind} {params.sif} echo {params.out} > {output.variables}57        singularity exec --bind {params.bind} {params.sif} echo {wildcards.pool} >> {output.variables}58        singularity exec --bind {params.bind} {params.sif} Rscript {params.script} {output.variables}59        [[ -s {output.figure} ]]60        echo $?61        """62####################################################63############ SCRIPT TO PRODUCE QC PLOTS ############64####################################################65rule echo_final_assignments:66    input:67        expand(output_dict["output_dir"] + "/{pool}/CombinedResults/Final_Assignments_demultiplexing_doublets.txt", pool = samples.Pool)68    output:69        output_dict["output_dir"] + "/QC_figures/final_assignments.txt"70    resources:71        mem_per_thread_gb=1,72        disk_per_thread_gb=173    threads: 174    params:75        sif = input_dict["singularity_image"],76        bind = bind_path77    log: output_dict["output_dir"] + "/logs/echo_final_assignments.log"78    shell:79        """80        singularity exec --bind {params.bind} {params.sif} echo {input} | singularity exec --bind {params.bind} {params.sif} tr ' ' '\n' >> {output}81        """82rule final_assignments_check:83    input:84        assignment_list = output_dict["output_dir"] + "/QC_figures/final_assignments.txt",85        meta=input_dict["samplesheet_filepath"]86    output:87        assignment_list = output_dict["output_dir"] + "/QC_figures/final_assignments_comparison.txt",88        meta = output_dict["output_dir"] + "/QC_figures/meta_comparison.txt"89    resources:90        mem_per_thread_gb=1,91        disk_per_thread_gb=192    threads: 193    params:94        sif = input_dict["singularity_image"],95        bind = bind_path96    log: output_dict["output_dir"] + "/logs/final_assignments_check.log"97    shell:98        """99        singularity exec --bind {params.bind} {params.sif} cat {input.assignment_list} > {output.assignment_list}100        singularity exec --bind {params.bind} {params.sif} awk 'BEGIN{{FS=OFS="\t"}}{{print $1}}' {input.meta} | singularity exec --bind {params.bind} {params.sif} tail -n+2 > {output.meta}101        if [ "$(wc -l < {output.meta})" -eq "$(wc -l < {output.assignment_list})" ]102        then 103            echo 0104        else 105            echo "The number of pools in the final_assignments.txt file don't match the number of pools in your sample sheet" > {log}106            rm {input.assignment_list}107            rm {output.assignment_list}108            rm {output.meta}109            echo 1110        fi111        """112rule expected_observed_numbers:113    input:114        final_assignment = output_dict["output_dir"] + "/QC_figures/final_assignments.txt",115        sample_sheet = input_dict["samplesheet_filepath"]116    output:117        report(output_dict["output_dir"] + "/QC_figures/expected_observed_individuals_classifications.png", category = "Number Individuals Summary", caption = "../report_captions/expected_observed_numbers.rst")118    resources:119        mem_per_thread_gb = lambda wildcards, attempt: attempt * CombineResults_dict["expected_observed_numbers_memory"],120        disk_per_thread_gb = lambda wildcards, attempt: attempt * CombineResults_dict["expected_observed_numbers_memory"]121    threads: CombineResults_dict["expected_observed_numbers_threads"]122    params:123        sif = input_dict["singularity_image"],124        bind = bind_path,125        script = "/opt/WG1-pipeline-QC/Demultiplexing/scripts/expected_observed_individuals_doublets.R",126        out = output_dict["output_dir"] + "/QC_figures/",127        basedir = output_dict["output_dir"]128    log: output_dict["output_dir"] + "/logs/expected_observed_numbers.log"129    shell:130        """131        singularity exec --bind {params.bind} {params.sif} Rscript {params.script} {input.sample_sheet} {params.out} {params.basedir}132        """133rule QC_plots:134    input:135        assignment_list = output_dict["output_dir"] + "/QC_figures/final_assignments_comparison.txt",136        pools = output_dict["output_dir"] + "/QC_figures/meta_comparison.txt"137    output:138        variables = temp(output_dict["output_dir"] + "/QC_figures/R_variables.txt"),139        fig1 = report(output_dict["output_dir"] + "/QC_figures/nCount_RNA_violin_MAD_All.png", category = "QC", caption = "../report_captions/QC_plots_nCount.rst"),140        fig2 = report(output_dict["output_dir"] + "/QC_figures/nCount_RNA_violin_MADper_Pool.png", category = "QC", caption = "../report_captions/QC_plots_nCount_RNA_MADall.rst"),141        fig3 = report(output_dict["output_dir"] + "/QC_figures/nCount_RNA_violin_noMADlines.png", category = "QC", caption = "../report_captions/QC_plots_nCount.rst"),142        fig4 = report(output_dict["output_dir"] + "/QC_figures/nFeature_RNA_violin_MAD_All.png", category = "QC", caption = "../report_captions/QC_plots_feature_MADall.rst"),143        fig5 = report(output_dict["output_dir"] + "/QC_figures/nFeature_RNA_violin_MADper_Pool.png", category = "QC", caption = "../report_captions/QC_plots_feature_MADperPool.rst"),144        fig6 = report(output_dict["output_dir"] + "/QC_figures/nFeature_RNA_violin_noMADlines.png", category = "QC", caption = "../report_captions/QC_plots_feature.rst"),145        fig7 = report(output_dict["output_dir"] + "/QC_figures/nFeatures_vs_percentMT_QC_scatter_colorPool.png", category = "QC", caption = "../report_captions/QC_plots_features_mt_pool.rst"),146        fig8 = report(output_dict["output_dir"] + "/QC_figures/nFeatures_vs_percentMT_QC_scatter_w_MADlines.png", category = "QC", caption = "../report_captions/QC_plots_features_mt_MAD.rst"),147        fig9 = report(output_dict["output_dir"] + "/QC_figures/percent.mt_violin_MAD_All.png", category = "QC", caption = "../report_captions/QC_plots_mt_MADall.rst"),148        fig10 = report(output_dict["output_dir"] + "/QC_figures/percent.mt_violin_MADper_Pool.png", category = "QC", caption = "../report_captions/QC_plots_mt_MADpool.rst"),149        fig11 = report(output_dict["output_dir"] + "/QC_figures/percent.mt_violin_noMADlines.png", category = "QC", caption = "../report_captions/QC_plots_mt.rst"),150        fig12 = report(output_dict["output_dir"] + "/QC_figures/percent.rb_violin_MAD_All.png", category = "QC", caption = "../report_captions/QC_plots_rb_MADall.rst"),151        fig13 = report(output_dict["output_dir"] + "/QC_figures/percent.rb_violin_MADper_Pool.png", category = "QC", caption = "../report_captions/QC_plots_rb_MADperPool.rst"),152        fig14 = report(output_dict["output_dir"] + "/QC_figures/percent.rb_violin_noMADlines.png", category = "QC", caption = "../report_captions/QC_plots_rb.rst"),153        fig15 = report(output_dict["output_dir"] + "/QC_figures/UMI_vs_Genes_QC_scatter.png", category = "QC", caption = "../report_captions/QC_plots_UMI_features.rst"),154        fig16 = report(output_dict["output_dir"] + "/QC_figures/UMI_vs_Genes_QC_scatter_w_MADlines.png", category = "QC", caption = "../report_captions/QC_plots_UMI_features_MADall.rst"),155        fig17 = report(output_dict["output_dir"] + "/QC_figures/UMI_vs_percentMT_QC_scatter_colorPool.png", category = "QC", caption = "../report_captions/QC_plots_UMI_mt_pool.rst"),156        fig18 = report(output_dict["output_dir"] + "/QC_figures/UMI_vs_percentMT_QC_scatter_w_MADlines.png", category = "QC", caption = "../report_captions/QC_plots_UMI_mt_MDA_all.rst"),157    resources:158        mem_per_thread_gb = lambda wildcards, attempt: attempt * CombineResults_dict["FinalQC_memory"],159        disk_per_thread_gb = lambda wildcards, attempt: attempt * CombineResults_dict["FinalQC_memory"]160    threads: CombineResults_dict["FinalQC_threads"]161    params:162        sif = input_dict["singularity_image"],163        bind = bind_path,164        script = "/opt/WG1-pipeline-QC/Demultiplexing/scripts/Singlet_QC_Figures.R",165        main_dir = output_dict["output_dir"],166        dirs10x = output_dict["output_dir"] + '/file_directories.txt',167        out = output_dict["output_dir"] + "/QC_figures/",168        rb_genes = "/opt/WG1-pipeline-QC/Demultiplexing/Ribosomal_genes.txt",169        mt_genes = "/opt/WG1-pipeline-QC/Demultiplexing/Mitochondrial_genes.txt"170    log: output_dict["output_dir"] + "/logs/QC_plots.log"171    shell:172        """173        singularity exec --bind {params.bind} {params.sif} echo {params.main_dir} > {output.variables}174        singularity exec --bind {params.bind} {params.sif} echo {input.pools} >> {output.variables}175        singularity exec --bind {params.bind} {params.sif} echo {params.dirs10x} >> {output.variables}176        singularity exec --bind {params.bind} {params.sif} echo {params.out} >> {output.variables}177        singularity exec --bind {params.bind} {params.sif} echo {params.rb_genes} >> {output.variables}178        singularity exec --bind {params.bind} {params.sif} echo {params.mt_genes} >> {output.variables}179        singularity exec --bind {params.bind} {params.sif} Rscript {params.script} {output.variables}180        [[ -s {output.fig18} ]]181        echo $?...

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