SECEDO: SNV-based subclone detection using ultra-low coverage single-cell DNA sequencing.

ABSTRACT:

Motivation

Several recently developed single-cell DNA sequencing technologies enable whole-genome sequencing of thousands of cells. However, the ultra-low coverage of the sequenced data (<0.05× per cell) mostly limits their usage to the identification of copy number alterations in multi-megabase segments. Many tumors are not copy number-driven, and thus single-nucleotide variant (SNV)-based subclone detection may contribute to a more comprehensive view on intra-tumor heterogeneity. Due to the low coverage of the data, the identification of SNVs is only possible when superimposing the sequenced genomes of hundreds of genetically similar cells. Thus, we have developed a new approach to efficiently cluster tumor cells based on a Bayesian filtering approach of relevant loci and exploit

SUBMITTER: Rozhonova H 

PROVIDER: S-EPMC9477524 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature