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

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

American journal of human genetics - 8 Jan 2015

Zhu Xiaofeng, Feng Tao, Tayo Bamidele O, Liang Jingjing, Young J Hunter, Franceschini Nora, Smith Jennifer A, Yanek Lisa R, Sun Yan V, Edwards Todd L, Chen Wei, Nalls Mike, Fox Ervin, Sale Michele, Bottinger Erwin, Rotimi Charles, Liu Yongmei, McKnight Barbara, Liu Kiang, Arnett Donna K, Chakravati Aravinda, Cooper Richard S, Redline Susan

Abstract excerpt

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data...

Read the complete abstract on PubMed

Topics

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

Share to Blood Pressure
Share to IGFBP3 gene

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetic Loci

Share to Genome-Wide Association Study

Share to Hypertension

Share to Models, Biological

Share to Phenotype

Share to Polymorphism, Single Nucleotide

Source

Open in PubMed Open full text

Identifiers

PMID: 25500260
DOI: 10.1016/j.ajhg.2014.11.011
PMCID: PMC4289691

Genes

CDH17
CHIC2
EVX1
IGFBP1
IGFBP3
WNT3

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

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.PMID 25500260Read ↗

GWAShug: a comprehensive platform for decoding the shared genetic basis between complex traits based on summary statistics.Semantic proximity Read ↗

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.Semantic proximity Read ↗

Cross-Phenotype Association Analysis Using Summary Statistics from GWAS.Semantic proximity Read ↗

Dissecting the genetics of complex traits using summary association statisticsSemantic proximity Read ↗

Dissecting the genetics of complex traits using summary association statistics.Semantic proximity Read ↗

Methods for meta-analysis of multiple traits using GWAS summary statistics.Semantic proximity Read ↗

A custom correlation coefficient (CCC) approach for fast identification of multi-SNP association patterns in genome-wide SNPs data.Semantic proximity Read ↗

Variance-component-based meta-analysis of gene-environment interactions for rare variants.Semantic proximity Read ↗

Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets.Semantic proximity Read ↗

Association analysis of rare and common variants with multiple traits based on variable reduction method.Semantic proximity Read ↗

Integration of Multiple-Omics Data to Analyze the Population-Specific Differences for Coronary Artery Disease.Semantic proximity Read ↗

A Powerful Method for Pleiotropic Analysis under Composite Null Hypothesis Identifies Novel Shared Loci Between Type 2 Diabetes and Prostate CancerSemantic proximity Read ↗

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