Assessing the performance of methods for copy number aberration detection from single-cell DNA sequencing data.

ABSTRACT: Single-cell DNA sequencing technologies are enabling the study of mutations and their evolutionary trajectories in cancer. Somatic copy number aberrations (CNAs) have been implicated in the development and progression of various types of cancer. A wide array of methods for CNA detection has been either developed specifically for or adapted to single-cell DNA sequencing data. Understanding the strengths and limitations that are unique to each of these methods is very important for obtaining accurate copy number profiles from single-cell DNA sequencing data. We benchmarked three widely used methods-Ginkgo, HMMcopy, and CopyNumber-on simulated as well as real datasets. To facilitate this, we developed a novel simulator of single-cell genome evolution in the presence of CNAs. Furthermore, to a

SUBMITTER: Mallory XF 

PROVIDER: S-EPMC7377518 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature