On single-cell RNA-sequencing data, we consider the problem of assigning cells to known cell types, assuming that the identities of cell-type-specific marker genes are given but their exact expression levels are unavailable, that is, without using a reference dataset. Based on an observation that the expected over-expression of marker genes is often absent in a nonnegligible proportion of cells, we develop a method called scSorter. scSorter allows marker genes to express at a low level and borrows information from the expression of non-marker genes. On both simulated and real data, scSorter shows much higher power compared to existing methods.
CITATION STYLE
Guo, H., & Li, J. (2021). scSorter: assigning cells to known cell types according to marker genes. Genome Biology, 22(1). https://doi.org/10.1186/s13059-021-02281-7
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