Briefings in BioinformaticsBioinformaticsPeer-reviewed journal article
CosGeneGate Selects Multi-functional and Credible Biomarkers for Single-cell Analysis
Tianyu LiuiD, Wenxin LongiD, Zhiyuan CaoiD, Yuge WangiD, Chuan Hua He, Le ZhangiD, Stephen M. StrittmatteriD, Hongyu ZhaoiD
Abstract
Selecting representative genes or marker genes to distinguish cell types is an important task in single-cell sequencing analysis. Although many methods have been proposed to select marker genes, the genes selected may have redundancy and/or do not show cell-type-specific expression patterns to distinguish cell types. Here we present a novel model, named CosGeneGate, to select marker genes for more effective marker selections. CosGeneGate is inspired by combining the advantages of selecting marker genes based on both cell-type classification accuracy and marker gene specific expression patterns. We demonstrate the better performance of the marker genes selected by CosGeneGate for various downstream analyses than the existing methods with both public datasets and newly sequenced datasets. The non-redundant marker genes identified by CosGeneGate for major cell types and tissues in human can be found at the website as follows: https://github.com/VivLon/CosGeneGate/blob/main/marker gene list.xlsx.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 9
- FWCI
- 1.22
- Field percentile
- top 22%
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