nf-core pipeline · alternative-splicing, rna, rna-seq
nf-core/rnasplice
An RNA sequencing pipeline for analysing alternative splicing, differential transcript usage, and exon usage.
What nf-core/rnasplice is
nf-core/rnasplice is a bioinformatics workflow designed for alternative splicing analysis of RNA sequencing data. It applies to organisms that have an available reference genome and annotation, providing multiple analytical routes to evaluate alternative isoform dynamics across experimental conditions.
Originally developed by the bioinformatics team at Zifo RnD Solutions and maintained by the Genomics Facility at the Istituto Italiano di Tecnologia, the pipeline integrates several established statistical methods to detect differential transcript usage, differential exon usage, event-based splicing, and intron clustering within a single pipeline.
What the pipeline does
The workflow begins by merging technical replicate FASTQ files and assessing initial read quality with FastQC. Adapter sequences and poor-quality bases are trimmed using TrimGalore. Reads are aligned against the reference genome using STAR, or optionally quantified via Salmon pseudo-alignment. Genome alignments are sorted and indexed with SAMtools, and normalised coverage tracks are generated as bigWig files with BEDTools and bedGraphToBigWig. QC metrics from each step are aggregated into an overview report via MultiQC.
For splicing assessment, the pipeline provides multiple modular downstream paths. Differential exon usage is measured by quantifying reads with HTSeq or featureCounts, followed by statistical evaluation with DEXSeq or edgeR. Differential transcript usage is quantified with Salmon and tested via DRIMSeq and DEXSeq or through IsoformSwitchAnalyzeR. Event-based splicing changes are identified and quantified with rMATS or SUPPA2, while intron excision clusters can optionally be profiled using RegTools and LeafCutter.
Key facts
- Pipeline engine
- Nextflow
- Latest release
- 1.0.4
- Input formats
- FASTQ (single-end or paired-end), CSV (samplesheet and contrast sheet)
- Output formats
- BAM, bigWig, HTML reports, tabular quantification and differential testing files
- Alignment tools
- STAR, Salmon (pseudo-alignment)
- Differential exon tools
- HTSeq, featureCounts, DEXSeq, edgeR
- Differential transcript tools
- Salmon, DRIMSeq, DEXSeq, IsoformSwitchAnalyzeR
- Event and intron tools
- rMATS, SUPPA2, RegTools, LeafCutter
What you can use it for
- Differential exon usage
- Quantifying exon-level features from STAR alignments using HTSeq or featureCounts, followed by differential testing across conditions using DEXSeq or edgeR.
- Differential transcript usage and switching
- Evaluating transcript abundance with Salmon to detect isoform switches with IsoformSwitchAnalyzeR or proportion changes with DRIMSeq and DEXSeq.
- Event-based splicing quantification
- Detecting specific alternative splicing events, such as skipped exons or retained introns, using rMATS from BAM alignments or SUPPA2 from transcript quantifications.
- Intron cluster excision analysis
- Extracting splice junctions with RegTools and evaluating differential intron excision patterns with LeafCutter.
Run it here
The research agent runs nf-core/rnasplice 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
- Supports multiple distinct analytical approaches to splicing, including exon-level, transcript-level, event-based, and intron cluster quantification.
- Automates data hygiene by merging lane replicates, trimming adapters, indexing alignments, and aggregating quality metrics into MultiQC reports.
- Provides flexibility between full splice-aware genomic alignment with STAR and pseudo-alignment with Salmon.
Watch out for
- Requires study organisms to possess a pre-existing reference genome and transcript annotation.
- Pipeline execution parameters cannot be passed via custom configuration files with the Nextflow -c flag and must be supplied via CLI options or parameter files.
- LeafCutter intron cluster quantification is an optional component requiring specific pipeline flag activation.
Questions
Can I run nf-core/rnasplice without my own cluster?
The research agent runs nf-core/rnasplice 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/rnasplice under?
MIT, like every nf-core pipeline.
What inputs are necessary to run nf-core/rnasplice?
The pipeline requires a CSV samplesheet defining single-end or paired-end FASTQ paths with strandedness and condition labels, a CSV contrast sheet defining sample comparisons, and reference genome files.
How are re-sequenced or multi-lane samples handled?
Entries in the samplesheet containing identical sample identifiers are treated as technical replicates and automatically concatenated using cat prior to trimming and alignment.
Which methods are available for differential exon usage?
Users can generate counts using HTSeq (DEXSeq count) or featureCounts, and test for differential exon usage using either DEXSeq or edgeR.
Can the pipeline process unstranded RNA-seq data?
Yes, but library strandedness must be explicitly declared for each sample in the samplesheet.
How to cite it
10.5281/zenodo.8424632
Written from nf-core/rnasplice's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.