A hidden Markov modeling approach for identifying tumor subclones in next-generation sequencing studies.

ABSTRACT: Allele-specific copy number alteration (ASCNA) analysis is for identifying copy number abnormalities in tumor cells. Unlike normal cells, tumor cells are heterogeneous as a combination of dominant and minor subclones with distinct copy number profiles. Estimating the clonal proportion and identifying mainclone and subclone genotypes across the genome are important for understanding tumor progression. Several ASCNA tools have recently been developed, but they have been limited to the identification of subclone regions, and not the genotype of subclones. In this article, we propose subHMM, a hidden Markov model-based approach that estimates both subclone region and region-specific subclone genotype and clonal proportion. We specify a hidden state variable representing the conglomeration of c

SUBMITTER: Choo-Wosoba H 

PROVIDER: S-EPMC9119345 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature