
splicekit is a modular platform for splicing analysis from short-read RNA-seq datasets. It integrates a JBrowse2 instance, pybio for genomic operations and scanRBP for RNA-protein binding studies. The whole analysis is self-contained in a single project folder, and the platform itself is written in Python, in a modular way.
Check a short video presentation about splicekit (poster) at ECCB 2023 on YouTube:
No installation needed: splicekit is integrated into expressRNA.org and runs automatically as part of every Differential Gene Expression analysis on bulk RNA-seq data. Once a DGE analysis finishes, expressRNA triggers splicekit in the background and adds an Alternative Splicing panel with browsable, searchable junction/exon/gene-level results (FDR < 0.05), downloadable splicekit.config/samples.tab, and a linked JBrowse2 view — all in the browser, no local setup required.
Since version 0.7, splicekit is a Snakemake pipeline, with a Conda/micromamba environment file.
git clone git@github.com:bedapub/splicekit.git # clone repo
cd splicekit # change working directory
micromamba create -y -f splicekit.yaml # create conda env
micromamba activate splicekit # activate env
./install.sh # install dependencies
pip install . # install splicekit
cd datasets/GSE126543 # move to sample folder
./1_download.sh # download sample FASTQs
pybio homo_sapiens # human genome
./run_snakemake_local.sh --configfile config.yaml # run snakemake (local)
./run_snakemake_slurm.sh --configfile config.yaml # OR run snakemake SLURMAfter Snakemake finishes, explore the results interactively by running splicekit web and following the printed instructions to open the HTML report in your browser.
Installing splicekit directly from the GitHub repository
pip install git+https://github.com/bedapub/splicekit.git@main
If you already have aligned reads in BAM files
All you need is samples.tab (note that this is a TAB delimited file) and splicekit.config in one folder (check datasets for examples).
You can easily download and prepare the reference genome (e.g. pybio genome homo_sapiens).
Finally, run ./run_snakemake_[local/slurm].sh --configfile config.yaml inside the folder with samples.tab and splicekit.config.
The easiest way to see what these files should look like is to check the datasets examples — they also include scripts for mapping FASTQ files to BAM with pybio if you need that step too.
Full documentation, including installation, a quick start guide, and reference pages for configuration, sample annotation, features, edgeR, motif/scanRBP analysis, juDGE plots, additional analyses, JBrowse2 and the command line, is available at:
Docs: released in September 2026
- migrated documentation to a mkdocs-material site (bedapub.github.io/splicekit), retiring the PDF/Google Docs manual
v0.8.1: released in July 2026
- added
bam_filecolumn support insamples.tabfor per-sample BAM paths (subfolder layouts) - new
get_bam_path(sample_id)helper insplicekit/core/annotation.py— falls back to{bam_path}/{sample_id}.bamwhen no per-sample path is given exons.py,genes.py,anchors.py: replacedos.listdir()BAM discovery withannotation.sampleslist +get_bam_path()(enables subfolder BAMs, no dir scan needed)junctions.py,jbrowse2.py: sameget_bam_path()adoption- default
bam_column = "bam_file"added to config
v0.8: released in October 2025
- removed platform config option (now snakemake submits jobs to the cluster)
- pandas and other minor improvements
v0.7: released in February 2025
- Snakemake version
- Conda splicekit.yaml for environment setup
Past change notes (click to view)
v0.6: released in April 2024
- updated reports
- JUNE analysis (junction-events to classify skipped and mutually exclusive exons)
v0.4.9: released in November 2023
- added rMATS analysis for splicing events
- added Docker container that can be directly imported to singularity via ghcr.io
- fixed dependencies
- other small fixes
v0.4: released in May 2023
- added singularity container with all dependencies
- added local integrated JBrowse2
- cluster or desktop runs
- scanRBP and bootstrap analysis of RNA-protein binding
- further development and integration with pybio
- extended documentation of concepts, analysis and results
v0.3: released in January 2023 (click to show details)
- re-coded junction analysis
- independent junctions parsing from provided bam files
- master table of all junctions in the samples of the analyzed project, including novel junctions (refseq/ensembl non-annotated)
- clustering by logFC of pairwise-comparisons with dendrogram: junction, exon and gene levels (clusterlogfc module)
- added first_exon annotation for junctions touching annotated first exons of transcripts
- extended documentation of concepts, analysis and results
v0.2: released in October 2022
- software architecture restructure with python modules
- filtering of lowly expressed features by edgeR
- DonJuan analysis (junction-anchor analysis)
- more advanced motif analysis with DREME
- filtering regulated junctions with regulated donors
v0.1: released in July 2022
- initial version of splicekit
- parsing of junction and exon counts
- computing edgeR analysis from count tables and producing a results file with direct links to JBrowse2
- basic motif analysis
If you find splicekit useful in your work and research, please cite:
Rot, G., Wehling, A., Schmucki, R., Berntenis, N., Zhang, J. D., & Ebeling, M. (2024)
splicekit : an integrative toolkit for splicing analysis from short-read RNA-seq
Bioinformatics Advances, 4(1). https://doi.org/10.1093/bioadv/vbae121
In case of questions, issues and other ideas, please use the GitHub Issues or write directly to Gregor Rot.
