Apr 9, 2015

MEGSA: A powerful and flexible framework for analyzing mutual exclusivity of tumor mutations

BioRxiv : the Preprint Server for Biology
Xing HuaJianxin Shi

Abstract

The central challenge in tumor sequencing studies is to identify driver genes and pathways, investigate their functional relationships and nominate drug targets. The efficiency of these analyses, particularly for infrequently mutated genes, is compromised when patients carry different combinations of driver mutations. Mutual exclusivity analysis helps address these challenges. To identify mutually exclusive gene sets (MEGS), we developed a powerful and flexible analytic framework based on a likelihood ratio test and a model selection procedure. Extensive simulations demonstrated that our method outperformed existing methods for both statistical power and the capability of identifying the exact MEGS, particularly for highly imbalanced MEGS. Our method can be used for de novo discovery, pathway-guided searches or for expanding established small MEGS. We applied our method to the whole exome sequencing data for fourteen cancer types from The Cancer Genome Atlas (TCGA). We identified multiple previously unreported non-pairwise MEGS in multiple cancer types. For acute myeloid leukemia, we identified a novel MEGS with five genes ( FLT3, IDH2, NRAS, KIT and TP53 ) and a MEGS ( NPM1, TP53 and RUX1 )s whose mutation status was strongly ...Continue Reading

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Mentioned in this Paper

TP53 gene
Study
Biochemical Pathway
FLT3
NRAS gene
N-ras Genes
AKT1
Genome
Genes
RAC-Alpha Serine/Threonine Kinase

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