nf-core pipeline · chloroplast-genome, genome, genome-skimming
nf-core/genomeskim
Performs quality control, filtering, and organelle assembly or genome analysis from genome skimming data.
What nf-core/genomeskim is
nf-core/genomeskim is a bioinformatics analysis pipeline designed for handling genome skims, which are low-coverage sequencing runs commonly used to recover high-copy cellular components. Originally developed by Thomas J. Creedy, the workflow provides standardised quality control, filtering, and downstream organellar assembly or genome analysis.
The pipeline is engineered within the nf-core framework using Nextflow DSL2, isolating software dependencies into individual process containers. It supports reproducible execution across varied computing platforms, including high-performance clusters and cloud architectures.
What the pipeline does
The workflow ingests sequencing reads specified via a samplesheet. It executes initial quality assessment using FastQC and aggregates read quality metrics into a comprehensive report using MultiQC.
Following quality control and read filtering steps, the pipeline carries out organellar genome assembly—focusing on mitochondrial and chloroplast genomes—and associated genomic analysis.
Key facts
- Pipeline engine
- Nextflow (DSL2)
- Original author
- Thomas J. Creedy
- Input format
- Sample sheet (CSV) specifying sequence data
- Read QC software
- FastQC, MultiQC
- Target genomes
- Chloroplast and mitochondrial genomes
- Supported container engines
- Docker, Singularity, Podman, Shifter, Charliecloud, Conda
What you can use it for
- Organelle genome assembly
- Assembling chloroplast and mitochondrial genomes from shallow genome skimming read data.
- Sequencing read quality inspection
- Evaluating raw read quality profiles using FastQC and producing unified inspection reports with MultiQC.
- Genome skim data filtering
- Preprocessing and filtering genome skimming sequences prior to downstream genomic analyses.
Run it here
The research agent runs nf-core/genomeskim 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
- Uses Nextflow DSL2 with dedicated software containers per process to ensure portable and reproducible results across compute environments.
- Undergoes automated continuous integration benchmarking on full-sized datasets using AWS cloud infrastructure.
- Compatible with a wide variety of container runtimes, including Docker, Singularity, Podman, Shifter, and Charliecloud.
Watch out for
- Requires Nextflow version 21.10.3 or higher.
- Conda software management is advised only as an environment configuration of last resort relative to containerised runtimes.
Questions
Can I run nf-core/genomeskim without my own cluster?
The research agent runs nf-core/genomeskim 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/genomeskim under?
MIT, like every nf-core pipeline.
What types of genomic assemblies does nf-core/genomeskim perform?
The pipeline is designed to perform organelle assembly, including both chloroplast and mitochondrial genomes, from genome skimming datasets.
Which tools are used for initial quality control?
The pipeline runs FastQC to assess raw read quality and collates the findings into an interactive summary report using MultiQC.
How are inputs provided to the pipeline?
Inputs are supplied using a CSV samplesheet via the --input command-line argument.
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/genomeskim's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.