bioRxivBioinformaticsPreprint
SVelfie: A method for discovering cancer drivers based on enrichment of likely functional structural variants
Xavi LoinaziD, Johnathan Dagan, Jean-Baptiste AlbergeiD, Antonia KowalewskiiD, Mendy L. MilleriD, Julian M. HessiD, Esther RheinbayiD, Chip StewartiD, Gad A. GetziD
Abstract
Structural variants (SVs) can drive tumorigenesis, yet discovering SV cancer drivers remains challenging1. Here, we present SVelfie (Structural Variants enriched with likely functional/impactful events), a statistical method to infer driver genes from SVs detected across a cohort of cancer genomes, based on enrichment of likely functional events. When testing SVelfie on lymphoma samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG)2, it corroborates known tumor suppressor genes and also yields novel driver candidates.
- organism: human
- assay: whole-genome sequencing
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 1
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