Sensitivity to sequencing depth in single-cell cancer genomics.

ABSTRACT:

Background

Querying cancer genomes at single-cell resolution is expected to provide a powerful framework to understand in detail the dynamics of cancer evolution. However, given the high costs currently associated with single-cell sequencing, together with the inevitable technical noise arising from single-cell genome amplification, cost-effective strategies that maximize the quality of single-cell data are critically needed. Taking advantage of previously published single-cell whole-genome and whole-exome cancer datasets, we studied the impact of sequencing depth and sampling effort towards single-cell variant detection.

Methods

Five single-cell whole-genome and whole-exome cancer datasets were independently downscaled to 25, 10, 5, and 1× sequencing depth. For each depth l

SUBMITTER: Alves JM 

PROVIDER: S-EPMC5901877 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature