DNAsmash pipeline

a fast paired-end DNA mapping pipeline using URMAP from .fastq or .bam files for sample swap detection of matched files using SMaSH SNPs in maftools

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set up pipeline

before running, you have to set up the attached Docker image:

docker build -t dnasmash-pipeline https://raw.githubusercontent.com/loipf/DNAsmash-pipeline/master/docker/Dockerfile

now either replace the Docker container hash (last output line from previous build command) in nextflow.config or run nextflow with the -with-docker dnasmash-pipeline argument.

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run pipeline

URMAP index must fit into memory, so at least 32Gb RAM are necessary.

it can be run locally with downloaded github-repo and edited nextflow.config file with:

nextflow run main.nf

or

nextflow run loipf/DNAsmash-pipeline -r main --project_dir /path/to/folder --sample_list /path/to/list --num_threads 10 -with-docker dnasmash-pipeline

for this execution to work properly, you have to be in the current project directory.

the --sample_list option file must contain the folder path of each sample where the raw reads (.fq.gz|.fastq.gz) or already mapped reads (.bam+.bam.bai) are located (without any empty lines):

/path/to/reads_raw/sample1
/path/to/reads_mapped/sample3
/path/to/reads_raw/sample2
/path/to/reads_mapped/sample4

optional extendable with:

-resume
-with-report report_DNAsmash-pipeline
-with-timeline timeline_DNAsmash-pipeline
-w work_dir

by default, all output will be saved into the data folder of the current directory. best to run with a new clear folder structure as not all new results do overwrite old ones.