This repository is a community-curated list of software packages, data resources, tutorials, and publications for single-cell data analysis. It serves researchers and bioinformaticians working with various single-cell modalities, including RNA-seq and ATAC-seq, aiming to provide a comprehensive and up-to-date overview of available tools.

How It Works

The list is organized by analysis task, covering a wide spectrum from quality control and normalization to advanced methods like trajectory inference, gene regulatory network identification, and multi-omics integration. It highlights tools written in various programming languages (R, Python, MATLAB, C++, Julia, Go) and often links to their GitHub repositories, documentation, and relevant publications.

Quick Start & Requirements

• Installation typically involves standard package managers like pip or conda, or direct installation from source (e.g., R/Bioconductor packages).
• Many tools require specific versions of Python, R, or system libraries, and some may benefit from or require GPU acceleration (e.g., for deep learning models).
• Specific dataset requirements vary by tool, but many are designed to work with standard single-cell data formats like AnnData or Seurat objects.

Highlighted Details

• Extensive coverage of single-cell RNA-seq analysis, including specialized tools for doublet identification, imputation, and copy number analysis.
• Dedicated sections for epigenomics (ATAC-seq, DNA methylation) and multi-omics integration, reflecting the growing complexity of single-cell research.
• A comprehensive catalog of spatial transcriptomics tools, covering deconvolution, alignment, and visualization.
• Includes a curated list of influential papers, method comparisons, and web portals for broader context and resource discovery.

Maintenance & Community

The list is community-curated, with contributions actively welcomed. It features prominent researchers and labs in the single-cell field, indicating a vibrant and active community.

Licensing & Compatibility

Licenses vary widely across the listed tools, ranging from permissive MIT and BSD licenses to more restrictive GPL licenses. Users must check individual tool licenses for compatibility with commercial or closed-source projects.

Limitations & Caveats

As a curated list, the "awesomeness" and completeness are subjective and depend on community contributions. The rapid pace of single-cell tool development means some entries may become outdated, and users should always verify the current status and maintenance of individual packages.