SCONCE: a method for profiling copy number alterations in cancer evolution using single-cell whole genome sequencing.

ABSTRACT:

Motivation

Copy number alterations (CNAs) are a significant driver in cancer growth and development, but remain poorly characterized on the single cell level. Although genome evolution in cancer cells is Markovian through evolutionary time, CNAs are not Markovian along the genome. However, existing methods call copy number profiles with Hidden Markov Models or change point detection algorithms based on changes in observed read depth, corrected by genome content and do not account for the stochastic evolutionary process.

Results

We present a theoretical framework to use tumor evolutionary history to accurately call CNAs in a principled manner. To model the tumor evolutionary process and account for technical noise from low coverage single-cell whole genome sequencing data, we

SUBMITTER: Hui S 

PROVIDER: S-EPMC8963318 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature