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Approved research

Statistical methods for high-dimensional phenotypes in UK Biobank

Principal Investigator: Professor Jonathan Marchini
Approved Research ID: 11626
Approval date: September 1st 2015

Lay summary

We will apply methods for analysis of multiple correlated traits to high-dimensional phenotypic data and genotype data, in order to a) predict missing phenotypes in the complete dataset, which will be of interest to other UK Biobank reserachers b) infer graphical models between phenotypes that allow inference of the underlying genetic correlation between traits c) apply mutiple trait GWAS to UK Biobank samples for a selected range of phenotypes The research will provide useful imputed phenotypic data for other UK Biobank researchers, aid with understanding the genetic correlation between traits, develop tools that scale to high-dimensional traits in large sample sizes and uncover novel associations. We will apply our existing statistical methods to the data We would like all samples for which genotype data and imputed data is available