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- W3109624723 abstract "Abstract The variation in gene expression profiles of cells captured in different phases of the cell cycle can interfere with cell type identification and functional analysis of single cell RNA-Seq (scRNA-Seq) data. In this paper, we introduce SC1CC ( SC1 C ell C ycle analysis tool), a computational approach for clustering and ordering single cell transcriptional profiles according to their progression along cell cycle phases. We also introduce a new robust metric, Gene Smoothness Score (GSS) for assessing the cell cycle based order of the cells. SC1CC is available as part of the SC1 web-based scRNA-Seq analysis pipeline, publicly accessible at https://sc1.engr.uconn.edu/ ." @default.
- W3109624723 created "2020-12-07" @default.
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- W3109624723 date "2020-11-22" @default.
- W3109624723 modified "2023-10-17" @default.
- W3109624723 title "Computational cell cycle analysis of single cell RNA-Seq data" @default.
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- W3109624723 doi "https://doi.org/10.1101/2020.11.21.392613" @default.
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