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SnapATAC2: Single-cell epigenomics analysis pipeline

Project description

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

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[!TIP] Got raw fastq files? Check out our new single-cell preprocessing package 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.

Documentation

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

SnapATAC2 is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse® and want to support our mission, please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

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