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

Principal components of heritability for high dimension quantitative traits and general pedigrees.

Statistical applications in genetics and molecular biology - 6 Jan 2012

Oualkacha Karim, Labbe Aurelie, Ciampi Antonio, Roy Marc-Andre, Maziade Michel

Abstract excerpt

For many complex disorders, genetically relevant disease definition is still unclear. For this reason, researchers tend to collect large numbers of items related directly or indirectly to the disease diagnostic. Since the measured traits may not be all influenced by genetic factors, researchers are faced with the problem of choosing which traits or combinations of traits to consider in linkage analysis. To...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Bipolar Disorder

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

Share to Computer Simulation

Share to Genetic Linkage

Share to Models, Genetic

Share to Principal Component Analysis

Share to Quantitative Trait, Heritable

Share to Schizophrenia

Source

Identifiers

PMID: 22499698
DOI: 10.2202/1544-6115.1711

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

Principal components of heritability for high dimension quantitative traits and general pedigrees.PMID 22499698Read ↗

Pleiotropy and principal components of heritability combine to increase power for association analysis.Semantic proximity Read ↗

Comparison of Heritability Estimation and Linkage Analysis for Multiple Traits Using Principal Component Analyses.Semantic proximity Read ↗

A principal-components approach based on heritability for combining phenotype information.Semantic proximity Read ↗

Principal components methods for narrow-sense heritability in the analysis of multidimensional longitudinal cognitive phenotypes.Semantic proximity Read ↗

Covariance component models for multivariate binary traits in family data analysis.Semantic proximity Read ↗

Variance-components methods for linkage and association analysis of ordinal traits in general pedigrees.Semantic proximity Read ↗

Principal components of heritability from neurocognitive domains differ between families with schizophrenia and control subjects.Semantic proximity Read ↗

An Effective Method to Identify Heritable Components from Multivariate Phenotypes.Semantic proximity Read ↗

A comparison of principal component analysis and factor analysis strategies for uncovering pleiotropic factors.Semantic proximity Read ↗

Testing association and maternally mediated genetic effects with the principal component analysis in case-parents studies.Semantic proximity Read ↗

Tests of association between quantitative traits and haplotypes in a reduced-dimensional space.Semantic proximity Read ↗

Mapping quantitative trait loci using multiple phenotypes in general pedigrees.Semantic proximity Read ↗

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