Somatic Structural Variation Discovery in Multiple Cancer Genomes
Calvin Lab
We present a novel method for detecting and genotyping somatic structural variations (SVs) in multiple whole-genome sequencing (WGS) tumor samples, taken from a cancer patient. In contrast to standard SV discovery approaches in cancer genomes, which do not leverage phylogenetic information, we make use of the multi-sample lineage tree structure reconstructed from ultra-deep sequencing somatic SNV datasets. We demonstrate that leveraging lineage trees boosts sensitivity in detecting and genotyping of SVs. Our method effectively pools samples that share a common ancestor in the tree and finds clusters of discordant paired-end reads that suggest the same SV breakpoint across these samples. Placement of SVs onto specific branches of the lineage tree results in a more comprehensive roadmap of the tumor's genome evolution that begins at the zygote.