Article
Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk.
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology - 1 Dec 2016
MacInnis Robert J, Schmidt Daniel F, Makalic Enes, Severi Gianluca, FitzGerald Liesel M, Reumann Matthias, Kapuscinski Miroslaw K, Kowalczyk Adam, Zhou Zeyu, Goudey Benjamin, Qian Guoqi, Bui Quang M, Park Daniel J, Freeman Adam, Southey Melissa C, Al Olama Ali Amin, Kote-Jarai Zsofia, Eeles Rosalind A, Hopper John L, Giles Graham G
Abstract excerpt
BACKGROUND: We have developed a genome-wide association study analysis method called DEPTH (DEPendency of association on the number of Top Hits) to identify genomic regions potentially associated with disease by considering overlapping groups of contiguous markers (e.g., SNPs) across the genome. DEPTH is a machine learning algorithm for feature ranking of ultra-high dimensional datasets, built from...
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