2014/06/27 by Amit G. Deshwar, Deshwar, Amit G., Shankar Vembu +9
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Cancer Genomics and Diagnostics #Evolution and Genetic Dynamics #FOS: Biological sciences #FOS: Computer and information sciences #Genomics and Phylogenetic Studies #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Populations and Evolution (q-bio.PE) #cs.LG #q-bio.PE #stat.ML
paper · pdf · doi:10.48550/arxiv.1406.7250
openalex publication_date 2014/06/27 · arxiv created 2015/01/06 · arxiv updated 2015/01/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.