Article
MOAT: efficient detection of highly mutated regions with the Mutations Overburdening Annotations Tool.
Bioinformatics (Oxford, England) - 15 Mar 2018
Lochovsky Lucas, Zhang Jing, Gerstein Mark
Abstract excerpt
Summary: Identifying genomic regions with higher than expected mutation count is useful for cancer driver detection. Previous parametric approaches require numerous cell-type-matched covariates for accurate background mutation rate (BMR) estimation, which is not practical for many situations. Non-parametric, permutation-based approaches avoid this issue but usually suffer from considerable compute-time cost....
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