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

Copulas in QTL mapping.

Behavior genetics - 1 Mar 2004

Basrak Bojan, Klaassen Chris A J, Beekman Marian, Martin Nick G, Boomsma Dorret I

Abstract excerpt

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular,...

Read the complete abstract on PubMed

Topics

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

Share to Analysis of Variance
Share to Chromosome Mapping
Share to Likelihood Functions

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

Share to Lipoprotein(a)

Share to Models, Statistical

Share to Normal Distribution

Share to Quantitative Trait Loci

Share to Twins, Dizygotic

Source

Identifiers

PMID: 14755181
DOI: 10.1023/B:BEGE.0000013730.63991.ba

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

Copulas in QTL mapping.PMID 14755181Read ↗

A Gaussian copula approach for the analysis of secondary phenotypes in case-control genetic association studies.Semantic proximity Read ↗

A copula-based set-variant association test for bivariate continuous, binary or mixed phenotypes.Semantic proximity Read ↗

Variance component methods for detecting complex trait loci.Semantic proximity Read ↗

Estimating the power of variance component linkage analysis in large pedigrees.Semantic proximity Read ↗

Linkage mapping of quantitative trait loci in humans: an overview.Semantic proximity Read ↗

Smoothing of the bivariate LOD score for non-normal quantitative traits.Semantic proximity Read ↗

Functional mapping of dynamic traits with robust t-distribution.Semantic proximity Read ↗

Semiparametric variance components models for genetic studies with longitudinal phenotypes.Semantic proximity Read ↗

MCMC-based linkage analysis for complex traits on general pedigrees: multipoint analysis with a two-locus model and a polygenic component.Semantic proximity Read ↗

A flexible copula-based approach for the analysis of secondary phenotypes in ascertained samples.Semantic proximity Read ↗

Combining dependent F-tests for robust association of quantitative traits under genetic model uncertainty.Semantic proximity Read ↗

Linkage analysis for complex diseases using variance component analysis: SOLAR.Semantic proximity Read ↗

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