Chromosomal imbalances detected via RNA-sequencing in 28 cancers Journal Article


Authors: Ozcan, Z.; San Lucas, F. A.; Wong, J. W.; Chang, K.; Stopsack, K. H.; Fowler, J.; Jakubek, Y. A.; Scheet, P.
Article Title: Chromosomal imbalances detected via RNA-sequencing in 28 cancers
Abstract: Motivation: RNA-sequencing (RNA-seq) of tumor tissue is typically only used to measure gene expression. Here, we present a statistical approach that leverages existing RNA-seq data to also detect somatic copy number alterations (SCNAs), a pervasive phenomenon in human cancers, without a need to sequence the corresponding DNA. Results: We present an analysis of 4942 participant samples from 28 cancers in The Cancer Genome Atlas (TCGA), demonstrating robust detection of SCNAs from RNA-seq. Using genotype imputation and haplotype information, our RNA-based method had a median sensitivity of 85% to detect SCNAs defined by DNA analysis, at high specificity (∼95%). As an example of translational potential, we successfully replicated SCNA features associated with breast cancer subtypes. Our results credential haplotype-based inference based on RNA-seq to detect SCNAs in clinical and population-based settings. © 2022 The Author(s) 2022. Published by Oxford University Press.
Journal Title: Bioinformatics
Volume: 38
Issue: 6
ISSN: 1367-4803
Publisher: Oxford University Press  
Date Published: 2022-03-15
Start Page: 1483
End Page: 1490
Language: English
DOI: 10.1093/bioinformatics/btab861
PROVIDER: scopus
PMCID: PMC8896613
PUBMED: 34999743
DOI/URL:
Notes: Article -- Export Date: 1 April 2022 -- Source: Scopus
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