Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.11.11.376467v1?rss=1 Authors: Chattopadhyay, S., Karlsson, J., Valind, A., Andersson, N., Gisselsson, D. Abstract: To understand the evolutionary dynamics of cancer, clonal deconvolution of mutational landscapes across multiple biopsies from the same patient is crucial. However, the frequencies of mutated alleles are often distorted by variation in copy number of mutated loci as well as the purity across samples. We present a semi-supervised algorithm that normalizes for purity and incorporates allelic composition with bulk sequencing to reliably segregate clonal/subclonal variants even at low sequencing depth (~50x). In presence of at least one tumor sample with >70% purity, it deconvolves samples down to ~40% purity, allowing robust tracking of mutated cell populations through cancer evolution. Copy rights belong to original authors. Visit the link for more info