Chromosomal imbalances detected via RNA-sequencing in 28 cancers.

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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.\nRESULTS: 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.\nAVAILABILITY AND IMPLEMENTATION: The analyses presented use the data publicly available from TCGA Research Network (http://cancergenome.nih.gov/). See Methods for details regarding data downloads. hapLOHseq software is freely available under The MIT license and can be downloaded from http://scheet.org/software.html.\nSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.", "claims": [{"id": "claim-method", "statement": "To identify genomic regions that harbor SCNAs, we applied hapLOHseq.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34999743", "locator": "sections[11] \"3 Results\" paragraph 3", "quote": "To identify genomic regions that harbor SCNAs, we applied hapLOHseq."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The analyses presented use the data publicly available from TCGA Research Network (http://cancergenome.nih.gov/). 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