Scelestial: Fast and accurate single-cell lineage tree inference based on a Steiner tree approximation algorithm.

ABSTRACT: Single-cell genome sequencing provides a highly granular view of biological systems but is affected by high error rates, allelic amplification bias, and uneven genome coverage. This creates a need for data-specific computational methods, for purposes such as for cell lineage tree inference. The objective of cell lineage tree reconstruction is to infer the evolutionary process that generated a set of observed cell genomes. Lineage trees may enable a better understanding of tumor formation and growth, as well as of organ development for healthy body cells. We describe a method, Scelestial, for lineage tree reconstruction from single-cell data, which is based on an approximation algorithm for the Steiner tree problem and is a generalization of the neighbor-joining method. We adapt the algorit

SUBMITTER: Foroughmand-Araabi MH 

PROVIDER: S-EPMC9426887 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature