https://github.com/scverse/snapatac2
Single-cell epigenomics analysis tools
https://github.com/scverse/snapatac2
single-cell-genomics
Last synced: 3 months ago
JSON representation
Single-cell epigenomics analysis tools
- Host: GitHub
- URL: https://github.com/scverse/snapatac2
- Owner: scverse
- Created: 2021-12-04T03:09:16.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2025-06-30T14:08:49.000Z (3 months ago)
- Last Synced: 2025-07-01T05:03:46.785Z (3 months ago)
- Topics: single-cell-genomics
- Language: Python
- Homepage: https://scverse.org/SnapATAC2
- Size: 23.9 MB
- Stars: 264
- Watchers: 9
- Forks: 34
- Open Issues: 55
-
Metadata Files:
- Readme: README.md
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
SnapATAC2: A Python/Rust package for single-cell epigenomics analysis
=====================================================================
> [!TIP]
> Got raw fastq files? Check out our new single-cell preprocessing package [precellar](https://github.com/regulatory-genomics/precellar)!
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.
[//]: # (numfocus-fiscal-sponsor-attribution)
SnapATAC2 is part of the scverse® project ([website](https://scverse.org), [governance](https://scverse.org/about/roles)) and is fiscally sponsored by [NumFOCUS](https://numfocus.org/).
If you like scverse® and want to support our mission, please consider making a tax-deductible [donation](https://numfocus.org/donate-to-scverse) to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
Documentation
-------------
- **Full Documentation**: https://scverse.org/SnapATAC2/
- **Installation instructions**: https://scverse.org/SnapATAC2/install.html
- **Tutorial/Demo**: https://scverse.org/SnapATAC2/tutorials/index.html
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