# Research Object Crate for TronFlow alignment pipeline

Original URL: https://workflowhub.eu/workflows/418/ro_crate?version=1

# TronFlow alignment pipeline ![GitHub tag (latest SemVer)](https://img.shields.io/github/v/release/tron-bioinformatics/tronflow-bwa?sort=semver) [![Run tests](https://github.com/TRON-Bioinformatics/tronflow-bwa/actions/workflows/automated_tests.yml/badge.svg?branch=master)](https://github.com/TRON-Bioinformatics/tronflow-bwa/actions/workflows/automated_tests.yml) [![DOI](https://zenodo.org/badge/327943420.svg)](https://zenodo.org/badge/latestdoi/327943420) [![License](https://img.shields.io/badge/license-MIT-green)](https://opensource.org/licenses/MIT) [![Powered by Nextflow](https://img.shields.io/badge/powered%20by-Nextflow-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://www.nextflow.io/) The TronFlow alignment pipeline is part of a collection of computational workflows for tumor-normal pair somatic variant calling. Find the documentation here [![Documentation Status](https://readthedocs.org/projects/tronflow-docs/badge/?version=latest)](https://tronflow-docs.readthedocs.io/en/latest/?badge=latest) This pipeline aligns paired and single end FASTQ files with BWA aln and mem algorithms and with BWA mem 2. For RNA-seq STAR is also supported. To increase sensitivity of novel junctions use `--star_two_pass_mode` (recommended for RNAseq variant calling). It also includes an initial step of read trimming using FASTP. ## How to run it Run it from GitHub as follows: ``` nextflow run tron-bioinformatics/tronflow-alignment -profile conda --input_files $input --output $output --algorithm aln --library paired ``` Otherwise download the project and run as follows: ``` nextflow main.nf -profile conda --input_files $input --output $output --algorithm aln --library paired ``` Find the help as follows: ``` $ nextflow run tron-bioinformatics/tronflow-alignment --help N E X T F L O W ~ version 19.07.0 Launching `main.nf` [intergalactic_shannon] - revision: e707c77d7b Usage: nextflow main.nf --input_files input_files [--reference reference.fasta] Input: * input_fastq1: the path to a FASTQ file (incompatible with --input_files) * input_files: the path to a tab-separated values file containing in each row the sample name and two paired FASTQs (incompatible with --fastq1 and --fastq2) when `--library paired`, or a single FASTQ file when `--library single` Example input file: name1 fastq1.1 fastq1.2 name2 fastq2.1 fastq2.2 * reference: path to the indexed FASTA genome reference or the star reference folder in case of using star Optional input: * input_fastq2: the path to a second FASTQ file (incompatible with --input_files, incompatible with --library paired) * output: the folder where to publish output (default: output) * algorithm: determines the BWA algorithm, either `aln`, `mem`, `mem2` or `star` (default `aln`) * library: determines whether the sequencing library is paired or single end, either `paired` or `single` (default `paired`) * cpus: determines the number of CPUs for each job, with the exception of bwa sampe and samse steps which are not parallelized (default: 8) * memory: determines the memory required by each job (default: 32g) * inception: if enabled it uses an inception, only valid for BWA aln, it requires a fast file system such as flash (default: false) * skip_trimming: skips the read trimming step * star_two_pass_mode: activates STAR two-pass mode, increasing sensitivity of novel junction discovery, recommended for RNA variant calling (default: false) * additional_args: additional alignment arguments, only effective in BWA mem, BWA mem 2 and STAR (default: none) Output: * A BAM file \${name}.bam and its index * FASTP read trimming stats report in HTML format \${name.fastp_stats.html} * FASTP read trimming stats report in JSON format \${name.fastp_stats.json} ``` ### Input tables The table with FASTQ files expects two tab-separated columns without a header | Sample name | FASTQ 1 | FASTQ 2 | |----------------------|---------------------------------|------------------------------| | sample_1 | /path/to/sample_1.1.fastq | /path/to/sample_1.2.fastq | | sample_2 | /path/to/sample_2.1.fastq | /path/to/sample_2.2.fastq | ### Reference genome The reference genome has to be provided in FASTA format and it requires two set of indexes: * FAI index. Create with `samtools faidx your.fasta` * BWA indexes. Create with `bwa index your.fasta` For bwa-mem2 a specific index is needed: ``` bwa-mem2 index your.fasta ``` For star a reference folder prepared with star has to be provided. In order to prepare it will need the reference genome in FASTA format and the gene annotations in GTF format. Run a command as follows: ``` STAR --runMode genomeGenerate --genomeDir $YOUR_FOLDER --genomeFastaFiles $YOUR_FASTA --sjdbGTFfile $YOUR_GTF ``` ## References * Li H. and Durbin R. (2010) Fast and accurate long-read alignment with Burrows-Wheeler Transform. Bioinformatics, Epub. https://doi.org/10.1093/bioinformatics/btp698 * Shifu Chen, Yanqing Zhou, Yaru Chen, Jia Gu; fastp: an ultra-fast all-in-one FASTQ preprocessor, Bioinformatics, Volume 34, Issue 17, 1 September 2018, Pages i884–i890, https://doi.org/10.1093/bioinformatics/bty560 * Vasimuddin Md, Sanchit Misra, Heng Li, Srinivas Aluru. Efficient Architecture-Aware Acceleration of BWA-MEM for Multicore Systems. IEEE Parallel and Distributed Processing Symposium (IPDPS), 2019. * Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013 Jan 1;29(1):15-21. doi: 10.1093/bioinformatics/bts635. Epub 2012 Oct 25. PMID: 23104886; PMCID: PMC3530905.

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License
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## Contents

Main Workflow: TronFlow alignment pipeline
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