Nature CommunicationsCancer BiologyPeer-reviewed journal article
SVclone: inferring structural variant cancer cell fraction
M. Cmero, C. S. Ong, K. Yuan, J. Schröder, K. Mo, PCAWG Evolution and Heterogeneity Working Group, N. M. Corcoran, A. T. Papenfuss, C. M. Hovens, F. Markowetz, G. Macintyre
Abstract
We present SVclone, a computational method for inferring the cancer cell fraction of structural variant breakpoints from whole-genome sequencing data. We validate our approach using simulated and real tumour samples, and demonstrate its utility on 2,778 whole-genome sequenced tumours. We find a subset of liver, breast and ovarian cancer cases with decreased overall survival that have subclonally enriched copy-number neutral rearrangements, an observation that could not be discovered with currently available methods.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: differential expression
- approach: deep learning
- approach: statistical model
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