Integrative inference of subclonal tumour evolution from single-cell and bulk sequencing data.

ABSTRACT: Understanding the clonal architecture and evolutionary history of a tumour poses one of the key challenges to overcome treatment failure due to resistant cell populations. Previously, studies on subclonal tumour evolution have been primarily based on bulk sequencing and in some recent cases on single-cell sequencing data. Either data type alone has shortcomings with regard to this task, but methods integrating both data types have been lacking. Here, we present B-SCITE, the first computational approach that infers tumour phylogenies from combined single-cell and bulk sequencing data. Using a comprehensive set of simulated data, we show that B-SCITE systematically outperforms existing methods with respect to tree reconstruction accuracy and subclone identification. B-SCITE provides high-fid

SUBMITTER: Malikic S 

PROVIDER: S-EPMC6588593 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature