nf-core pipeline · community-workflow, deep-mutational-scanning, genotype-phenotype
nf-core/deepmutscan
A bioinformatics pipeline for analysing deep mutational scanning data generated by shotgun DNA sequencing.
What nf-core/deepmutscan is
nf-core/deepmutscan is a bioinformatics pipeline designed for the analysis of deep mutational scanning (DMS) experiments using shotgun DNA sequencing. Deep mutational scanning systematically measures the functional effects of large numbers of sequence variants, providing insight into genotype-phenotype relationships.
The workflow was originally developed by Benjamin Wehnert and Max Stammnitz as part of the nf-core initiative. It provides a community-curated, scalable, and reproducible method to process sequencing data from high-throughput mutagenesis libraries.
What the pipeline does
The pipeline ingests single-end or paired-end sequencing reads defined in a tabular samplesheet. It performs initial quality control on raw reads using FastQC, followed by aggregated quality assessment and reporting across samples using MultiQC.
Key facts
- Original developers
- Benjamin Wehnert and Max Stammnitz
- Pipeline engine
- Nextflow
- Experimental assay
- Deep mutational scanning (DMS)
- Sequencing method
- Shotgun DNA sequencing
- Input formats
- CSV samplesheet, FASTQ (single-end or paired-end)
- Included tools
- FastQC, MultiQC
What you can use it for
- Deep mutational scanning analysis
- Analysing shotgun DNA sequencing libraries derived from high-throughput mutagenesis experiments.
- Genotype-to-phenotype mapping
- Processing sequencing data to investigate the functional consequences of genetic variants across targeted sequences.
- Sequencing data quality control
- Evaluating base-call quality, read distributions, and sample-wide statistics across raw sequencing runs using FastQC and MultiQC.
Run it here
The research agent runs nf-core/deepmutscan with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Provides a reproducible and scalable framework for shotgun-sequenced deep mutational scanning workflows.
- Supports both single-end and paired-end sequencing input through a standardised samplesheet.
- Integrates automated per-sample read quality control and aggregated multi-sample reporting.
Watch out for
- Requires pipeline execution parameters to be specified via the command-line interface or a dedicated parameter file rather than general configuration files.
- Input sequencing reads must strictly conform to a defined comma-separated samplesheet structure.
Questions
Can I run nf-core/deepmutscan without my own cluster?
The research agent runs nf-core/deepmutscan with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/deepmutscan under?
MIT, like every nf-core pipeline.
What type of data does nf-core/deepmutscan process?
It processes shotgun DNA sequencing reads from deep mutational scanning experiments, supplied as single-end or paired-end FASTQ files.
Which quality control tools are included?
Raw read quality assessment is carried out using FastQC, and summary reports across samples are generated using MultiQC.
How are inputs provided to the pipeline?
Inputs are supplied through a comma-separated samplesheet that lists sample names alongside paths to the corresponding FASTQ files.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/deepmutscan's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.