NcdDetect2: improved models of the site-specific mutation rate in cancer and driver detection with robust significance evaluation.

ABSTRACT:

Motivation

Understanding the mutational processes that act during cancer development is a key topic of cancer biology. Nevertheless, much remains to be learned, as a complex interplay of processes with dependencies on a range of genomic features creates highly heterogeneous cancer genomes. Accurate driver detection relies on unbiased models of the mutation rate that also capture rate variation from uncharacterized sources.

Results

Here, we analyse patterns of observed-to-expected mutation counts across 505 whole cancer genomes, and find that genomic features missing from our mutation-rate model likely operate on a megabase length scale. We extend our site-specific model of the mutation rate to include the additional variance from these sources, which leads to robust signific

SUBMITTER: Juul M 

PROVIDER: S-EPMC6330011 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature