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Uncovering cell identity through differential stability with Cepo
Hani Jieun Kim1,2,3, Kevin Wang1, Carissa Chen2,3
1School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia.
Abstract:
The use of single-cell RNA-sequencing (scRNA-seq) allows observation of different cells at multi-tiered complexity in the same microenvironment. To get insights into cell identity using scRNA-seq data, we present Cepo, which generates cell-type-specific gene statistics of differentially stable genes from scRNA-seq data to define cell identity. When applied to multiple datasets, Cepo outperforms current methods in assigning cell identity and enhances several cell identification applications such as cell-type characterisation, spatial mapping of single cells and lineage inference of single cells.
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