Software & Tools
Computational tools developed by the Kostka Lab
We develop and maintain open-source software tools for computational biology and genomic data analysis. Our tools are designed to be accessible, well-documented, and ready for integration into bioinformatics pipelines.
Featured Tools
- seillra - Low-rank approximation of the Sei DNA sequence-to-function model
- aenmd - R package for annotating predicted escape from nonsense-mediated decay (NMD)
- vaeda - Variational autoencoder for doublet detection in single-cell data (Python)
- scds - R/Bioconductor package for doublet detection in single-cell data
For questions about our software or to report issues, please contact us or submit an issue on GitHub.