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A subregion-based burden test for simultaneous identification of susceptibility loci and subregions within

TitleA subregion-based burden test for simultaneous identification of susceptibility loci and subregions within
Publication TypeJournal Article
Year of Publication2018
AuthorsZhu, B, Mirabello, L, Chatterjee, N
JournalGenet Epidemiol
Volume42
Pagination673-683
Date PublishedOct
ISBN Number0741-0395
Accession Number29931698
Keywords*burden test, *disease susceptibility genes, *Genetic Loci, *Genetic Predisposition to Disease, *rare variant association studies, *subset-based approach, Angiopoietin-like 4 Protein/genetics, Computer Simulation, Genetic Variation, Humans, Models, Genetic, Osteosarcoma/genetics, Phenotype, Sequence Analysis, DNA
Abstract

In rare variant association studies, aggregating rare and/or low frequency variants, may increase statistical power for detection of the underlying susceptibility gene or region. However, it is unclear which variants, or class of them, in a gene contribute most to the association. We proposed a subregion-based burden test (REBET) to simultaneously select susceptibility genes and identify important underlying subregions. The subregions are predefined by shared common biologic characteristics, such as the protein domain or functional impact. Based on a subset-based approach considering local correlations between combinations of test statistics of subregions, REBET is able to properly control the type I error rate while adjusting for multiple comparisons in a computationally efficient manner. Simulation studies show that REBET can achieve power competitive to alternative methods when rare variants cluster within subregions. In two case studies, REBET is able to identify known disease susceptibility genes, and more importantly pinpoint the unreported most susceptible subregions, which represent protein domains essential for gene function. R package REBET is available at https://dceg.cancer.gov/tools/analysis/rebet.

PMCID

PMC6185783