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

G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies.

Genetic epidemiology - 1 Sept 2016

Wang Miaoyan, Jakobsdottir Johanna, Smith Albert V, McPeek Mary Sara

Abstract excerpt

In a large-scale genetic association study, the number of phenotyped individuals available for sequencing may, in some cases, be greater than the study's sequencing budget will allow. In that case, it can be important to prioritize individuals for sequencing in a way that optimizes power for association with the trait. Suppose a cohort of phenotyped individuals is available, with some subset of them possibly...

Read the complete abstract on PubMed

Topics

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

Share to Genetic Association Studies
Share to Genotype
Share to Polymorphism, Single Nucleotide

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Quantitative Trait Loci

Share to Software

Source

Open in PubMed Open full text

Identifiers

PMID: 27256766
DOI: 10.1002/gepi.21982
PMCID: PMC5473612

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

G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies.PMID 27256766Read ↗

On the optimal design of genetic variant discovery studies.Semantic proximity Read ↗

Efficient study design for next generation sequencing.Semantic proximity Read ↗

Low-, high-coverage, and two-stage DNA sequencing in the design of the genetic association study.Semantic proximity Read ↗

Efficient association study design via power-optimized tag SNP selection.Semantic proximity Read ↗

Two-phase designs to follow-up genome-wide association signals with DNA resequencing studies.Semantic proximity Read ↗

Optimized sample selection for cost-efficient long-read population sequencing.Semantic proximity Read ↗

Optimized selection of unrelated subjects for whole-genome sequencing studies of rare high-penetrance alleles.Semantic proximity Read ↗

A sample selection strategy for next-generation sequencing.Semantic proximity Read ↗

Designing a multistage, SNP-based, genome screen for common diseases.Semantic proximity Read ↗

Two-phase sample selection strategies for design and analysis in post-genome wide association fine-mapping studiesSemantic proximity Read ↗

Two-phase stratified sampling designs for regional sequencing.Semantic proximity Read ↗

isGWAS: ultra-high-throughput, scalable and equitable inference of genetic associations with diseaseSemantic proximity Read ↗

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