mirror of
https://github.com/KevinMidboe/linguist.git
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bee7e55618
* Added nextflow language * Added main.nf to list of filenames * Fixed duplicate groovy scope * Removed hello-world example * Update grammar submodule * Removed main.nf from filenames * Added nextflow.config example
497 lines
13 KiB
Plaintext
Executable File
497 lines
13 KiB
Plaintext
Executable File
#!/usr/bin/env nextflow
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/*
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* This is free and unencumbered software released into the public domain.
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*
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* Anyone is free to copy, modify, publish, use, compile, sell, or
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* distribute this software, either in source code form or as a compiled
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* binary, for any purpose, commercial or non-commercial, and by any
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* means.
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*
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* In jurisdictions that recognize copyright laws, the author or authors
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* of this software dedicate any and all copyright interest in the
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* software to the public domain. We make this dedication for the benefit
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* of the public at large and to the detriment of our heirs and
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* successors. We intend this dedication to be an overt act of
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* relinquishment in perpetuity of all present and future rights to this
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* software under copyright law.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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* IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
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* OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
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* ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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* OTHER DEALINGS IN THE SOFTWARE.
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*
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* For more information, please refer to <http://unlicense.org/>
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*/
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/*
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* 'CalliNGS-NF' - A Nextflow pipeline for variant calling with NGS data
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*
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* This pipeline that reproduces steps from the GATK best practics of SNP
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* calling with RNAseq data procedure:
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* https://software.broadinstitute.org/gatk/guide/article?id=3891
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*
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* Anna Vlasova
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* Emilio Palumbo
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* Paolo Di Tommaso
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* Evan Floden
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*/
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/*
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* Define the default parameters
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*/
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params.genome = "$baseDir/data/genome.fa"
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params.variants = "$baseDir/data/known_variants.vcf.gz"
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params.blacklist = "$baseDir/data/blacklist.bed"
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params.reads = "$baseDir/data/reads/rep1_{1,2}.fq.gz"
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params.results = "results"
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params.gatk = '/usr/local/bin/GenomeAnalysisTK.jar'
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params.gatk_launch = "java -jar $params.gatk"
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log.info "C A L L I N G S - N F v 1.0"
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log.info "================================"
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log.info "genome : $params.genome"
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log.info "reads : $params.reads"
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log.info "variants : $params.variants"
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log.info "blacklist: $params.blacklist"
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log.info "results : $params.results"
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log.info "gatk : $params.gatk"
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log.info ""
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/*
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* Parse the input parameters
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*/
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GATK = params.gatk_launch
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genome_file = file(params.genome)
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variants_file = file(params.variants)
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blacklist_file = file(params.blacklist)
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reads_ch = Channel.fromFilePairs(params.reads)
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/**********
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* PART 1: Data preparation
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*
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* Process 1A: Create a FASTA genome index (.fai) with samtools for GATK
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*/
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process '1A_prepare_genome_samtools' {
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tag "$genome.baseName"
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input:
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file genome from genome_file
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output:
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file "${genome}.fai" into genome_index_ch
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script:
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"""
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samtools faidx ${genome}
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"""
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}
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/*
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* Process 1B: Create a FASTA genome sequence dictionary with Picard for GATK
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*/
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process '1B_prepare_genome_picard' {
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tag "$genome.baseName"
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input:
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file genome from genome_file
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output:
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file "${genome.baseName}.dict" into genome_dict_ch
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script:
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"""
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PICARD=`which picard.jar`
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java -jar \$PICARD CreateSequenceDictionary R= $genome O= ${genome.baseName}.dict
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"""
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}
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/*
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* Process 1C: Create STAR genome index file.
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*/
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process '1C_prepare_star_genome_index' {
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tag "$genome.baseName"
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input:
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file genome from genome_file
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output:
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file "genome_dir" into genome_dir_ch
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script:
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"""
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mkdir genome_dir
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STAR --runMode genomeGenerate \
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--genomeDir genome_dir \
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--genomeFastaFiles ${genome} \
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--runThreadN ${task.cpus}
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"""
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}
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/*
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* Process 1D: Create a file containing the filtered and recoded set of variants
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*/
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process '1D_prepare_vcf_file' {
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tag "$variantsFile.baseName"
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input:
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file variantsFile from variants_file
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file blacklisted from blacklist_file
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output:
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set file("${variantsFile.baseName}.filtered.recode.vcf.gz"), file("${variantsFile.baseName}.filtered.recode.vcf.gz.tbi") into prepared_vcf_ch
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script:
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"""
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vcftools --gzvcf $variantsFile -c \
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--exclude-bed ${blacklisted} \
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--recode | bgzip -c \
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> ${variantsFile.baseName}.filtered.recode.vcf.gz
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tabix ${variantsFile.baseName}.filtered.recode.vcf.gz
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"""
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}
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/*
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* END OF PART 1
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*********/
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/**********
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* PART 2: STAR RNA-Seq Mapping
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*
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* Process 2: Align RNA-Seq reads to the genome with STAR
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*/
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process '2_rnaseq_mapping_star' {
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tag "$replicateId"
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input:
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file genome from genome_file
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file genomeDir from genome_dir_ch
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set replicateId, file(reads) from reads_ch
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output:
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set replicateId, file('Aligned.sortedByCoord.out.bam'), file('Aligned.sortedByCoord.out.bam.bai') into aligned_bam_ch
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script:
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"""
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# ngs-nf-dev Align reads to genome
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STAR --genomeDir $genomeDir \
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--readFilesIn $reads \
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--runThreadN ${task.cpus} \
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--readFilesCommand zcat \
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--outFilterType BySJout \
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--alignSJoverhangMin 8 \
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--alignSJDBoverhangMin 1 \
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--outFilterMismatchNmax 999
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# 2nd pass (improve alignmets using table of splice junctions and create a new index)
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mkdir genomeDir
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STAR --runMode genomeGenerate \
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--genomeDir genomeDir \
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--genomeFastaFiles $genome \
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--sjdbFileChrStartEnd SJ.out.tab \
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--sjdbOverhang 75 \
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--runThreadN ${task.cpus}
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# Final read alignments
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STAR --genomeDir genomeDir \
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--readFilesIn $reads \
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--runThreadN ${task.cpus} \
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--readFilesCommand zcat \
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--outFilterType BySJout \
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--alignSJoverhangMin 8 \
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--alignSJDBoverhangMin 1 \
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--outFilterMismatchNmax 999 \
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--outSAMtype BAM SortedByCoordinate \
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--outSAMattrRGline ID:$replicateId LB:library PL:illumina PU:machine SM:GM12878
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# Index the BAM file
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samtools index Aligned.sortedByCoord.out.bam
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"""
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}
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/*
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* END OF PART 2
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******/
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/**********
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* PART 3: GATK Prepare Mapped Reads
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*
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* Process 3: Split reads that contain Ns in their CIGAR string.
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* Creates k+1 new reads (where k is the number of N cigar elements)
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* that correspond to the segments of the original read beside/between
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* the splicing events represented by the Ns in the original CIGAR.
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*/
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process '3_rnaseq_gatk_splitNcigar' {
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tag "$replicateId"
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input:
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file genome from genome_file
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file index from genome_index_ch
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file genome_dict from genome_dict_ch
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set replicateId, file(bam), file(index) from aligned_bam_ch
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output:
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set replicateId, file('split.bam'), file('split.bai') into splitted_bam_ch
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script:
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"""
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# SplitNCigarReads and reassign mapping qualities
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$GATK -T SplitNCigarReads \
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-R $genome -I $bam \
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-o split.bam \
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-rf ReassignOneMappingQuality \
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-RMQF 255 -RMQT 60 \
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-U ALLOW_N_CIGAR_READS \
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--fix_misencoded_quality_scores
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"""
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}
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/*
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* END OF PART 3
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******/
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/***********
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* PART 4: GATK Base Quality Score Recalibration Workflow
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*
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* Process 4: Base recalibrate to detect systematic errors in base quality scores,
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* select unique alignments and index
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*
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*/
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process '4_rnaseq_gatk_recalibrate' {
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tag "$replicateId"
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input:
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file genome from genome_file
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file index from genome_index_ch
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file dict from genome_dict_ch
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set replicateId, file(bam), file(index) from splitted_bam_ch
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set file(variants_file), file(variants_file_index) from prepared_vcf_ch
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output:
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set sampleId, file("${replicateId}.final.uniq.bam"), file("${replicateId}.final.uniq.bam.bai") into (final_output_ch, bam_for_ASE_ch)
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script:
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sampleId = replicateId.replaceAll(/[12]$/,'')
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"""
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# Indel Realignment and Base Recalibration
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$GATK -T BaseRecalibrator \
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--default_platform illumina \
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-cov ReadGroupCovariate \
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-cov QualityScoreCovariate \
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-cov CycleCovariate \
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-knownSites ${variants_file} \
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-cov ContextCovariate \
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-R ${genome} -I ${bam} \
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--downsampling_type NONE \
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-nct ${task.cpus} \
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-o final.rnaseq.grp
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$GATK -T PrintReads \
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-R ${genome} -I ${bam} \
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-BQSR final.rnaseq.grp \
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-nct ${task.cpus} \
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-o final.bam
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# Select only unique alignments, no multimaps
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(samtools view -H final.bam; samtools view final.bam| grep -w 'NH:i:1') \
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|samtools view -Sb - > ${replicateId}.final.uniq.bam
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# Index BAM files
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samtools index ${replicateId}.final.uniq.bam
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"""
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}
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/*
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* END OF PART 4
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******/
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/***********
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* PART 5: GATK Variant Calling
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*
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* Process 5: Call variants with GATK HaplotypeCaller.
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* Calls SNPs and indels simultaneously via local de-novo assembly of
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* haplotypes in an active region.
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* Filter called variants with GATK VariantFiltration.
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*/
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process '5_rnaseq_call_variants' {
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tag "$sampleId"
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input:
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file genome from genome_file
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file index from genome_index_ch
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file dict from genome_dict_ch
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set sampleId, file(bam), file(bai) from final_output_ch.groupTuple()
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output:
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set sampleId, file('final.vcf') into vcf_files
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script:
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"""
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# fix absolute path in dict file
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sed -i 's@UR:file:.*${genome}@UR:file:${genome}@g' $dict
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echo "${bam.join('\n')}" > bam.list
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# Variant calling
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$GATK -T HaplotypeCaller \
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-R $genome -I bam.list \
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-dontUseSoftClippedBases \
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-stand_call_conf 20.0 \
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-o output.gatk.vcf.gz
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# Variant filtering
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$GATK -T VariantFiltration \
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-R $genome -V output.gatk.vcf.gz \
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-window 35 -cluster 3 \
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-filterName FS -filter "FS > 30.0" \
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-filterName QD -filter "QD < 2.0" \
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-o final.vcf
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"""
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}
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/*
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* END OF PART 5
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******/
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/***********
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* PART 6: Post-process variants file and prepare for Allele-Specific Expression and RNA Editing Analysis
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*
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* Process 6A: Post-process the VCF result
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*/
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process '6A_post_process_vcf' {
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tag "$sampleId"
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publishDir "$params.results/$sampleId"
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input:
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set sampleId, file('final.vcf') from vcf_files
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set file('filtered.recode.vcf.gz'), file('filtered.recode.vcf.gz.tbi') from prepared_vcf_ch
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output:
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set sampleId, file('final.vcf'), file('commonSNPs.diff.sites_in_files') into vcf_and_snps_ch
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script:
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'''
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grep -v '#' final.vcf | awk '$7~/PASS/' |perl -ne 'chomp($_); ($dp)=$_=~/DP\\=(\\d+)\\;/; if($dp>=8){print $_."\\n"};' > result.DP8.vcf
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vcftools --vcf result.DP8.vcf --gzdiff filtered.recode.vcf.gz --diff-site --out commonSNPs
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'''
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}
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/*
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* Process 6B: Prepare variants file for allele specific expression (ASE) analysis
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*/
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process '6B_prepare_vcf_for_ase' {
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tag "$sampleId"
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publishDir "$params.results/$sampleId"
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input:
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set sampleId, file('final.vcf'), file('commonSNPs.diff.sites_in_files') from vcf_and_snps_ch
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output:
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set sampleId, file('known_snps.vcf') into vcf_for_ASE
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file('AF.histogram.pdf') into gghist_pdfs
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script:
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'''
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awk 'BEGIN{OFS="\t"} $4~/B/{print $1,$2,$3}' commonSNPs.diff.sites_in_files > test.bed
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vcftools --vcf final.vcf --bed test.bed --recode --keep-INFO-all --stdout > known_snps.vcf
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grep -v '#' known_snps.vcf | awk -F '\\t' '{print $10}' \
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|awk -F ':' '{print $2}'|perl -ne 'chomp($_); \
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@v=split(/\\,/,$_); if($v[0]!=0 ||$v[1] !=0)\
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{print $v[1]/($v[1]+$v[0])."\\n"; }' |awk '$1!=1' \
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>AF.4R
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gghist.R -i AF.4R -o AF.histogram.pdf
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'''
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}
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/*
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* Group data for allele-specific expression.
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*
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* The `bam_for_ASE_ch` emites tuples having the following structure, holding the final BAM/BAI files:
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*
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* ( sample_id, file_bam, file_bai )
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*
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* The `vcf_for_ASE` channel emits tuples having the following structure, holding the VCF file:
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*
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* ( sample_id, output.vcf )
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*
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* The BAMs are grouped together and merged with VCFs having the same sample id. Finally
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* it creates a channel named `grouped_vcf_bam_bai_ch` emitting the following tuples:
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*
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* ( sample_id, file_vcf, List[file_bam], List[file_bai] )
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*/
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bam_for_ASE_ch
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.groupTuple()
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.phase(vcf_for_ASE)
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.map{ left, right ->
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def sampleId = left[0]
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def bam = left[1]
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def bai = left[2]
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def vcf = right[1]
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tuple(sampleId, vcf, bam, bai)
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}
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.set { grouped_vcf_bam_bai_ch }
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/*
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* Process 6C: Allele-Specific Expression analysis with GATK ASEReadCounter.
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* Calculates allele counts at a set of positions after applying
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* filters that are tuned for enabling allele-specific expression
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* (ASE) analysis
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*/
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process '6C_ASE_knownSNPs' {
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tag "$sampleId"
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publishDir "$params.results/$sampleId"
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input:
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file genome from genome_file
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file index from genome_index_ch
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file dict from genome_dict_ch
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set sampleId, file(vcf), file(bam), file(bai) from grouped_vcf_bam_bai_ch
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output:
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file "ASE.tsv"
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script:
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"""
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echo "${bam.join('\n')}" > bam.list
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$GATK -R ${genome} \
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-T ASEReadCounter \
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-o ASE.tsv \
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-I bam.list \
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-sites ${vcf}
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"""
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}
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