Random Forests for Genetic Association Studies
نویسندگان
چکیده
منابع مشابه
Evaluation of random forests performance for genome-wide association studies in the presence of interaction effects
Random forests (RF) is one of a broad class of machine learning methods that are able to deal with large-scale data without model specification, which makes it an attractive method for genome-wide association studies (GWAS). The performance of RF and other association methods in the presence of interactions was evaluated using the simulated data from Genetic Analysis Workshop 16 Problem 3, with...
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The widespread availability of DNA from large population studies, the development of rapid throughput genotyping assays, and the identification of numerous polymorphisms in genes of interest make it easier to perform genetic association studies in humans. We consider these studies appropriate areas of research in relation to atherosclerosis, thrombosis, and vascular biology. In this issue, Drs ...
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ژورنال
عنوان ژورنال: Statistical Applications in Genetics and Molecular Biology
سال: 2011
ISSN: 1544-6115,2194-6302
DOI: 10.2202/1544-6115.1691