RT Journal Article
SR Electronic
T1 Inferring copy number variation from gene expression data: methods, comparisons, and applications to oncology
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.10.18.463991
DO 10.1101/2021.10.18.463991
A1 Boen, Joseph
A1 Wagner, Joel P.
A1 Di Nanni, Noemi
YR 2021
UL http://biorxiv.org/content/early/2021/10/19/2021.10.18.463991.abstract
AB Copy number variations (CNVs) are genomic events where the number of copies of a particular gene varies from cell to cell. Cancer cells are associated with somatic CNV changes resulting in gene amplifications and gene deletions. However, short of single-cell whole-genome sequencing, it is difficult to detect and quantify CNV events in single cells. In contrast, the rapid development of single-cell RNA sequencing (scRNA-seq) technologies has enabled easy acquisition of single-cell gene expression data. In this work, we employ three methods to infer CNV events from scRNA-seq data and provide a statistical comparison of the methods’ results. In addition, we combine the analysis of scRNA-seq and inferred CNV data to visualize and determine subpopulations and heterogeneity in tumor cell populations.Competing Interest StatementJPW is a shareholder of Novartis Pharmaceuticals.