Article

Large-Scale Sparse Regression for Multiple Responses with Applications to UK Biobank

2020-05-31

Abstract excerpt

In high-dimensional regression problems, often a relatively small subset of the features are relevant for predicting the outcome, and methods that impose sparsity on the solution are popular. When multiple correlated outcomes are available (multitask), reduced rank regression is an effective way to borrow strength and capture latent structures that underlie the data. Our proposal is motivated by the UK Biobank pop...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c3e5430d-499b-5a05-830b-973bb4d782b3
DOI: 10.1101/2020.05.30.125252

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Large-Scale Sparse Regression for Multiple Responses with Applications to UK BiobankDOI 10.1101/2020.05.30.125252Read

A Fast and Scalable Framework for Large-scale and Ultrahigh-dimensional Sparse Regression with Application to the UK BiobankSemantic proximity Read

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

Computationally efficient whole-genome regression for quantitative and binary traits.Semantic proximity Read

Sparse reduced-rank regression for integrating omics data.Semantic proximity Read

Sparse matrix factorization robust to sample sharing across GWASs reveals interpretable genetic components.Semantic proximity Read

Efficient penalized generalized linear mixed models for variable selection and genetic risk prediction in high-dimensional data.Semantic proximity Read

Sparse matrix factorization robust to sample sharing across GWAS reveals interpretable genetic componentsSemantic proximity Read

Convex approaches to isolate the shared and distinct genetic structures of subphenotypes in heterogeneous complex traitsSemantic proximity Read

Iterative Hard Thresholding in GWAS: Generalized Linear Models, Prior Weights, and Double SparsitySemantic proximity Read

Structured Sparse Low-Rank Regression Model for Brain-Wide and Genome-Wide Associations.Semantic proximity Read

Exploring the Genetic Patterns of Complex Diseases via the Integrative Genome-Wide Approach.Semantic proximity Read

Unified tests for fine-scale mapping and identifying sparse high-dimensional sequence associations.Semantic proximity Read