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Genetics

Factoring single-cell perturbations

Nature Methods volume 20, pages 1629–1630 (2023)Cite this article

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GSFA is a statistical model to automatically detect latent factors (or gene modules) in single-cell CRISPR screening.

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Fig. 1: GSFA.

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Acknowledgements

We thank all members of the Li laboratory for valuable discussions. This work was supported by the startup fund from the Center for Genetic Medicine Research at the Children’s National Hospital and National Institute of Health research grants R01-HG010753 and R01-HL168174 (B.S. and W.L.).

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Authors and Affiliations

  1. Center for Genetic Medicine Research, Children’s National Hospital, Washington, DC, USA

    Bicna Song & Wei Li

  2. Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA

    Bicna Song & Wei Li

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  1. Bicna Song
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  2. Wei Li
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Correspondence to Wei Li.

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The authors declare no competing interests.

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Song, B., Li, W. Factoring single-cell perturbations. Nat Methods 20, 1629–1630 (2023). https://doi.org/10.1038/s41592-023-02002-x

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