Computational cell cycle analysis of single cell RNA-Seq data

Moussa, M. M. R.; Mandoiu, I. I.

doi:10.1101/2020.11.21.392613

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bioRxiv · 10.1101/2020.11.21.392613

Computational cell cycle analysis of single cell RNA-Seq data

Moussa, M. M. R.·Mandoiu, I. I.

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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 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/.

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BibTeX RIS

Moussa, M. M. R., Mandoiu, I. I.. 2020-11-22. Computational cell cycle analysis of single cell RNA-Seq data. https://doi.org/10.1101/2020.11.21.392613

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