nf-core pipeline · infernal, ncrna, rfam
nf-core/ncrnannotator
Annotates non-coding RNA loci across genome assemblies using Rfam covariance models and Infernal.
What nf-core/ncrnannotator is
nf-core/ncrnannotator is a bioinformatics pipeline for genome-level non-coding RNA (ncRNA) annotation. Developed by Pedro Madrigal and Victoria Begley from the RNA Resources team at EMBL-EBI, it identifies and maps ncRNA loci across genome assemblies.
Annotating non-coding RNAs across large assemblies requires structural search tools that can be computationally intensive. The pipeline addresses this by applying clade-specific filtering to Rfam covariance models and chunking genomic sequences to run parallel searches, producing standardised structural annotations.
What the pipeline does
The pipeline begins by filtering Rfam covariance models to a designated taxonomic clade, with dedicated modes for vertebrates and invertebrates. The target genome assembly is then partitioned into sequence windows to facilitate parallel execution.
Each window is searched against the filtered Rfam models using Infernal's cmsearch. Subsequent parsing scripts filter hits against gathering (GA) score thresholds and resolve overlapping predictions before exporting the final annotations in GTF, GFF3, and BED formats, alongside a MultiQC summary report.
Key facts
- Input formats
- FASTA (genome assembly), Rfam CM (.cm), Rfam seed (.seed)
- Output formats
- GTF, GFF3, BED, MultiQC HTML report
- Core search tool
- Infernal (cmsearch)
- Reference database
- Rfam
- Supported modes
- Vertebrate and invertebrate taxonomic modes
- Pipeline engine
- Nextflow
What you can use it for
- Vertebrate ncRNA annotation
- Annotate non-coding RNA features across newly assembled vertebrate genomes using clade-filtered covariance models.
- Invertebrate ncRNA annotation
- Identify and map ncRNA loci across invertebrate assemblies using invertebrate-specific Rfam subsets.
- Multi-format feature generation
- Generate consistent GTF, GFF3, and BED annotation tracks for downstream genomic analyses without creating a custom samplesheet.
Run it here
The research agent runs nf-core/ncrnannotator 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
- Filters covariance models to the target clade prior to search, reducing unneeded computation and spurious hits.
- Splits genome assemblies into windows for distributed, parallel searching with Infernal cmsearch.
- Automatically applies Rfam gathering score thresholds and removes overlapping feature predictions.
- Accepts raw FASTA genomes directly via command-line arguments without requiring a pre-formatted samplesheet.
Watch out for
- Requires local availability of Rfam covariance model and seed files.
- Taxonomic awareness is restricted to configured modes such as vertebrates and invertebrates.
Questions
Can I run nf-core/ncrnannotator without my own cluster?
The research agent runs nf-core/ncrnannotator 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/ncrnannotator under?
MIT, like every nf-core pipeline.
What inputs are required to run nf-core/ncrnannotator?
The pipeline requires a genome assembly in FASTA format, an Rfam covariance model file (Rfam.cm), and an Rfam seed file (Rfam.seed). No samplesheet file is needed.
Which annotation file formats does the pipeline output?
The pipeline exports parsed non-coding RNA annotations in GTF, GFF3, and BED formats, accompanied by a MultiQC metrics report.
How are overlapping RNA predictions handled?
The pipeline includes a parsing step that resolves overlapping matches and enforces Rfam gathering (GA) score cut-offs.
What taxonomic modes are available?
The pipeline supports taxonomic filtering modes for vertebrate and invertebrate clades, such as the ensembl-vertebrates mode.
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/ncrnannotator's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.