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

Improving power and robustness for detecting genetic association with extreme-value sampling design.

Genetic epidemiology - 1 Dec 2011

Chen Hua Yun, Li Mingyao

Abstract excerpt

Extreme-value sampling design that samples subjects with extremely large or small quantitative trait values is commonly used in genetic association studies. Samples in such designs are often treated as "cases" and "controls" and analyzed using logistic regression. Such a case-control analysis ignores the potential dose-response relationship between the quantitative trait and the underlying trait locus and thus...

Read the complete abstract on PubMed

Topics

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

Share to Case-Control Studies
Share to Cholesterol, HDL
Share to Cross-Sectional Studies

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Models, Genetic

Share to Quantitative Trait, Heritable

Share to Quantitative Trait Loci

Share to Regression Analysis

Share to Selection Bias

Source

Identifiers

PMID: 22006659
DOI: 10.1002/gepi.20631

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

Improving power and robustness for detecting genetic association with extreme-value sampling design.PMID 22006659Read ↗

Extreme sampling design in genetic association mapping of quantitative trait loci using balanced and unbalanced case-control samples.Semantic proximity Read ↗

Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies.Semantic proximity Read ↗

Phenotypic extremes in rare variant study designs.Semantic proximity Read ↗

Two-stage extreme phenotype sequencing design for discovering and testing common and rare genetic variants: efficiency and power.Semantic proximity Read ↗

The impact of exposure-biased sampling designs on detection of gene-environment interactions in case-control studies with potential exposure misclassification.Semantic proximity Read ↗

On Robust Association Testing for Quantitative Traits and Rare Variants.Semantic proximity Read ↗

Exposure Enriched Case-Control (EECC) Design for the Assessment of Gene-Environment Interaction.Semantic proximity Read ↗

Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants.Semantic proximity Read ↗

Estimating interaction between genetic and environmental risk factors: efficiency of sampling designs within a cohort.Semantic proximity Read ↗

Bias-reduced estimators and confidence intervals for odds ratios in genome-wide association studies.Semantic proximity Read ↗

STEPS: an efficient prospective likelihood approach to genetic association analyses of secondary traits in extreme phenotype sequencing.Semantic proximity Read ↗

Correction for multiple testing in a gene region.Semantic proximity Read ↗

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