geneBasis: an iterative approach for unsupervised selection of targeted gene panels from scRNA-seq.
IF: 17.906
Cited by: 10


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.


Spatial Transcriptomics


Missarova, Alsu
Jain, Jaison
Butler, Andrew
Ghazanfar, Shila
Stuart, Tim
Brusko, Maigan
Wasserfall, Clive
Nick, Harry
Brusko, Todd
Atkinson, Mark
Satija, Rahul
Marioni, John C

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