geneBasis: an iterative approach for unsupervised selection of targeted gene panels from scRNA-seq.
Springer Science and Business Media LLC
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Missarova, A., Jain, J., Butler, A., Ghazanfar, S., Stuart, T., Brusko, M., Wasserfall, C., et al. (2021). geneBasis: an iterative approach for unsupervised selection of targeted gene panels from scRNA-seq.. Genome Biol, 22 (1) https://doi.org/10.1186/s13059-021-02548-z
scRNA-seq datasets are increasingly used to identify gene panels that can be probed using alternative technologies, such as spatial transcriptomics, where choosing the best subset of genes is vital. Existing methods are limited by a reliance on pre-existing cell type labels or by difficulties in identifying markers of rare cells. We introduce an iterative approach, geneBasis, for selecting an optimal gene panel, where each newly added gene captures the maximum distance between the true manifold and the manifold constructed using the currently selected gene panel. Our approach outperforms existing strategies and can resolve cell types and subtle cell state differences.
NIH HHS (OT2 OD026673, 1OT2OD026673-01, RM1HG011014-02, U54AI142766, K99HG011489-01)
Cancer Research UK (C9545/A29580)
NIAID NIH HHS (U54 AI142766)
leona m. and harry b. helmsley charitable trust (2004-03813)
royal society (gb) (NIF\R1\181950)
External DOI: https://doi.org/10.1186/s13059-021-02548-z
This record's URL: https://www.repository.cam.ac.uk/handle/1810/333091
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/