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.

How to cite#

The SnapATAC2 manuscript has not been published yet. The key algorithms used in SnapATAC2 have been described in the following papers:

  • Zhang, K. et al. A single-cell atlas of chromatin accessibility in the human genome. Cell 184, 5985-6001.e19 (2021).

  • Fang, R. et al. Comprehensive analysis of single cell ATAC-seq data with SnapATAC. Nat Commun 12, 1337 (2021).