Computational Cell Cycle Analysis of Single Cell RNA-Seq Data

被引:0
|
作者
Moussa, Marmar [1 ]
Mandoiu, Ion I. [2 ]
机构
[1] Univ Connecticut, Sch Med, Farmington, CT 06030 USA
[2] Univ Connecticut, Storrs, CT USA
基金
美国国家科学基金会;
关键词
scRNA-Seq; Cell cycle; Cell order; Gene smoothness score; REVEALS; GENES;
D O I
10.1007/978-3-030-79290-9_7
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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 Cell Cycle 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/.
引用
收藏
页码:71 / 87
页数:17
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