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• W3136299713 abstract "ABSTRACT Differentially expressed gene-based analysis have faced difficulties associated with the inflation of P-values because of both the large sample size and selection bias introduced by exploratory data analysis in single-cell transcriptomics. Here, we propose the concept of discriminative feature of cells (DFC), implemented by logistic regression with an adaptive LASSO penalty. Adaptive LASSO selects a small subset of genes to discriminate a population of interest. DFC well captured non-independent structure of expression patterns such as cell-type-specific markers, specific composition of gene expression, and subcategories of this cell population. DFC may complement existing methods for interpreting large data sets." @default.
• W3136299713 created "2021-03-29" @default.
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• W3136299713 date "2021-03-12" @default.
• W3136299713 modified "2023-10-12" @default.
• W3136299713 title "Discriminative feature of cells characterizes cell populations of interest by a small subset of genes" @default.
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• W3136299713 doi "https://doi.org/10.1101/2021.03.12.435089" @default.
• W3136299713 hasPublicationYear "2021" @default.
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