Reconstructing subclonal composition and evolution from whole genome sequencing of tumors

Deshwar, Amit G., Vembu, Shankar, Yung, Christina K., Jang, Gun Ho, Stein, Lincoln, Morris, Quaid

arXiv.org Machine Learning 

Tumors often contain multiple subpopulations of cancerous cells defined by distinct somatic mutations. We describe a new method, PhyloWGS, that can be applied to WGS data from one or more tumor samples to reconstruct complete genotypes of these subpopulations based on variant allele frequencies (VAFs) of point mutations and population frequencies of structural variations. We introduce a principled phylogenic correction for VAFs in loci affected by copy number alterations and we show that this correction greatly improves subclonal reconstruction compared to existing methods.

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