Arcane: Alignment-free single cell RNA-seq gene expression estimation

Arcane is a lightweight, alignment-free tool for scRNA-seq quantification. It turns droplet scRNAseq data, such as 10x Genomics FASTQ files, into a gene-by-cell count matrix:

arcane express --index myindex --R1 $R1-files --R2 $R2-files --out outfolder -c v3

📖 Documentation

Full documentation: https://rahmannlab.gitlab.io/arcane

• Installation — conda environment and prebuilt human/mouse indices
• Quickstart — from FASTQ to count matrix
• Building an index
• CLI reference — every subcommand and flag
• File formats

Quick install

git clone https://gitlab.com/rahmannlab/arcane
cd arcane
conda env create      # creates the `arcane` environment from environment.yml
conda activate arcane
pip install -e .

Prebuilt human and mouse indices are available at https://doi.org/10.5281/zenodo.17663235.

arcane is a multi-command tool (like git); --help works on any subcommand:

arcane --help
arcane express --help

Reproducing the paper

See the workflow folder and its README.md.

Citation

Zentgraf, J., Schmitz, J. E., Keller, A., Rahmann, S. Error Correction Algorithms for Efficient Gene Expression Quantification in Single Cell Transcriptomics. bioRxiv (2025). doi:10.1101/2025.11.27.690682

Support

In case of problems, file an issue in the issue tracker. See CHANGELOG.md for recent changes. Thank you!

License

MIT. (c) 2019-2026 Algorithmic Bioinformatics, Saarland University.

Building the docs locally

pip install mkdocs-material
mkdocs serve      # preview at http://127.0.0.1:8000
mkdocs build --strict