OncodriveCLUSTL: a sequence-based clustering method to identify cancer drivers.

ABSTRACT:

Motivation

Identification of the genomic alterations driving tumorigenesis is one of the main goals in oncogenomics research. Given the evolutionary principles of cancer development, computational methods that detect signals of positive selection in the pattern of tumor mutations have been effectively applied in the search for cancer genes. One of these signals is the abnormal clustering of mutations, which has been shown to be complementary to other signals in the detection of driver genes.

Results

We have developed OncodriveCLUSTL, a new sequence-based clustering algorithm to detect significant clustering signals across genomic regions. OncodriveCLUSTL is based on a local background model derived from the simulation of mutations accounting for the composition of tri- or pe

SUBMITTER: Arnedo-Pac C 

PROVIDER: S-EPMC6853674 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature