Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A multivariate regression approach to association analysis of a quantitative trait network.

Bioinformatics (Oxford, England) - 15 Jun 2009

Kim Seyoung, Sohn Kyung-Ah, Xing Eric P

Abstract excerpt

MOTIVATION: Many complex disease syndromes such as asthma consist of a large number of highly related, rather than independent, clinical phenotypes, raising a new technical challenge in identifying genetic variations associated simultaneously with correlated traits. Although a causal genetic variation may influence a group of highly correlated traits jointly, most of the previous association analyses considered...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Computational Biology
Share to Gene Regulatory Networks
Share to Genome-Wide Association Study

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Models, Genetic

Share to Phenotype

Share to Polymorphism, Single Nucleotide

Share to Quantitative Trait Loci

Share to Regression Analysis

Source

Open in PubMed Open full text

Identifiers

PMID: 19477989
DOI: 10.1093/bioinformatics/btp218
PMCID: PMC2687972

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A multivariate regression approach to association analysis of a quantitative trait network.PMID 19477989Read ↗

Joint variable selection and network modeling for detecting eQTLs.Semantic proximity Read ↗

Network-guided sparse regression modeling for detection of gene-by-gene interactions.Semantic proximity Read ↗

A Bayesian network-based framework to uncover the causal effects of genes on complex traits based on GWAS dataSemantic proximity Read ↗

A Bayesian network-based framework to uncover the causal effects of genes on complex traits based on GWAS dataSemantic proximity Read ↗

Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs.Semantic proximity Read ↗

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

Inferring a directed acyclic graph of phenotypes from GWAS summary statisticsSemantic proximity Read ↗

A Bayesian hierarchically structured prior for gene-based association testing with multiple traits in genome-wide association studies.Semantic proximity Read ↗

Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group Lasso.Semantic proximity Read ↗

A Regression-based Framework for Scalable Pathway-guided Search in Genome-wide Association StudiesSemantic proximity Read ↗

Graph-regularized dual Lasso for robust eQTL mapping.Semantic proximity Read ↗

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

⌁Select a neighboring publication to make it the new centre.