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SnapATAC2: A Python/Rust package for single-cell epigenomics analysis

SnapATAC2 is a flexible, versatile, and scalable single-cell omics analysis framework, featuring:

• Scale to more than 10 million cells.
• Blazingly fast preprocessing tools for BAM to fragment files conversion and count matrix generation.
• Matrix-free spectral embedding algorithm that is applicable to a wide range of single-cell omics data, including single-cell ATAC-seq, single-cell RNA-seq, single-cell Hi-C, and single-cell methylation.
• Efficient and scalable co-embedding algorithm for single-cell multi-omics data integration.
• End-to-end analysis pipeline for single-cell ATAC-seq data, including preprocessing, dimension reduction, clustering, data integration, peak calling, differential analysis, motif analysis, regulatory network analysis.
• Seamless integration with other single-cell analysis packages such as Scanpy.
• Implementation of fully backed AnnData.

Resources

• Full Documentation: https://kzhang.org/SnapATAC2/
• Installation instructions: https://kzhang.org/SnapATAC2/install.html
• Tutorial/Demo: https://kzhang.org/SnapATAC2/tutorials/index.html
• Benchmarks: https://github.com/kaizhang/single-cell-benchmark

How to cite

Zhang, K., Zemke, N. R., Armand, E. J. & Ren, B. (2024). A fast, scalable and versatile tool for analysis of single-cell omics data. Nature Methods, 1–11. https://doi.org/10.1038/s41592-023-02139-9