A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank.

ABSTRACT: The UK Biobank is a very large, prospective population-based cohort study across the United Kingdom. It provides unprecedented opportunities for researchers to investigate the relationship between genotypic information and phenotypes of interest. Multiple regression methods, compared with genome-wide association studies (GWAS), have already been showed to greatly improve the prediction performance for a variety of phenotypes. In the high-dimensional settings, the lasso, since its first proposal in statistics, has been proved to be an effective method for simultaneous variable selection and estimation. However, the large-scale and ultrahigh dimension seen in the UK Biobank pose new challenges for applying the lasso method, as many existing algorithms and their implementations are not scalab

SUBMITTER: Qian J 

PROVIDER: S-EPMC7641476 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature