A database of software tools for the analysis of single-cell RNA-seq data. To make it into the database software must be available for download and public use somewhere (CRAN, Bioconductor, PyPI, Conda, GitHub, Bitbucket, a private website etc). To view the database head to https://www.scRNA-tools.org.

This database is designed to be an overview of the currently available scRNA-seq analysis software, it is unlikely to be 100% complete or accurate but will be updated as new software becomes available.

We welcome contributions from the scRNA-seq community! If you would like to contribute please follow the have a look at the wiki or fill in the submission form on our website (https://www.scrna-tools.org/submit). Please be aware that by contributing you are agreeing to abide by the code of conduct.

If you are interested in joining the scRNA-tools team please contact us.

If you find the scRNA-tools database useful for your work please cite our publication:

Zappia L, Phipson B, Oshlack A. "Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database", PLOS Computational Biology (2018), DOI: 10.1371/journal.pcbi.1006245

@ARTICLE{,
  title       = "Exploring the single-cell {RNA-seq} analysis landscape with
                 the {scRNA-tools} database",
  author      = "Zappia, Luke and Phipson, Belinda and Oshlack, Alicia",
  journal     = "PLoS Computational Biology",
  volume      =  14,
  number      =  6,
  pages       = "e1006245",
  month       =  jun,
  year        =  2018,
  language    = "en",
  doi         = "10.1371/journal.pcbi.1006245",
  url         = "https://doi.org/10.1371/journal.pcbi.1006245",
}

If you make use of our analysis of the first 1000 tools in the database please also cite:

Zappia L, Theis FJ. "Over 1000 tools reveal trends in the single-cell RNA-seq analysis landscape", Genome Biology (2021), DOI: 10.1186/s13059-021-02519-4

@ARTICLE{,
  title    = "Over 1000 tools reveal trends in the single-cell {RNA-seq}
              analysis landscape",
  author   = "Zappia, Luke and Theis, Fabian J",
  journal  = "Genome Biol.",
  volume   =  22,
  number   =  1,
  pages    = "301",
  month    =  oct,
  year     =  2021,
  language = "en"
  doi      = "10.1186/s13059-021-02519-4",
  url      = "https://doi.org/10.1186/s13059-021-02519-4"
}