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

Power and sample sizes for linkage with extreme sampling under an oligogenic model for quantitative traits.

Behavior genetics - 1 Jan 2002

Heo Moonseong, Faith Myles S, Allison David B

Abstract excerpt

Extreme sampling of sibling pairs has been shown to be efficient in terms of statistical power and sample sizes (in number of sibling pairs needed to genotype) to detect a quantitative trait locus (QTL) when the residual distribution is normal. In the present study, the efficiency of extreme sampling strategies to detect each locus under an oligogenic model is analytically explored with a test statistic based on...

Read the complete abstract on PubMed

Topics

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

Share to Alleles
Share to Chromosome Mapping
Share to Gene Frequency

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Genetic Linkage

Share to Genotype

Share to Models, Genetic

Share to Models, Statistical

Share to Quantitative Trait, Heritable

Source

Identifiers

PMID: 11958540
DOI: 10.1023/a:1014403827957

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Power and sample sizes for linkage with extreme sampling under an oligogenic model for quantitative traits.PMID 11958540Read ↗

QTL mapping with discordant and concordant sibling pairs: new statistics and new design strategies.Semantic proximity Read ↗

Considerations on study designs using the extreme sibpairs methods under multilocus oligogenic models.Semantic proximity Read ↗

Mapping quantitative-trait loci in humans by use of extreme concordant sib pairs: selected sampling by parental phenotypes.Semantic proximity Read ↗

A unified framework for detecting rare variant quantitative trait associations in pedigree and unrelated individuals via sequence data.Semantic proximity Read ↗

Optimal selection of sib pairs from random samples for linkage analysis of a QTL using the EDAC test.Semantic proximity Read ↗

The power to detect linkage disequilibrium with quantitative traits in selected samples.Semantic proximity Read ↗

Selection of the most informative individuals from families with multiple siblings for association studies.Semantic proximity Read ↗

Combining extremely concordant sibpairs with extremely discordant sibpairs provides a cost effective way to linkage analysis of quantitative trait loci.Semantic proximity Read ↗

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

Effectiveness of extreme discordant sib pairs to detect oligogenic disease loci.Semantic proximity Read ↗

Identifying rare variants for quantitative traits in extreme samples of population via Kullback-Leibler distance.Semantic proximity Read ↗

Extreme discordant sib pairs for mapping quantitative trait loci in humans.Semantic proximity Read ↗

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