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

Bayesian robust analysis for genetic architecture of quantitative traits.

Bioinformatics (Oxford, England) - 15 Apr 2009

Yang Runqing, Wang Xin, Li Jian, Deng Hongwen

Abstract excerpt

MOTIVATION: In most quantitative trait locus (QTL) mapping studies, phenotypes are assumed to follow normal distributions. Deviations from this assumption may affect the accuracy of QTL detection and lead to detection of spurious QTLs. To improve the robustness of QTL mapping methods, we replaced the normal distribution for residuals in multiple interacting QTL models with the normal/independent distributions...

Read the complete abstract on PubMed

Topics

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

Share to Quantitative Trait Loci
Share to Bayes Theorem
Share to Computer Simulation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Crosses, Genetic

Share to Databases, Genetic

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 18974168
DOI: 10.1093/bioinformatics/btn558
PMCID: PMC2666810

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Bayesian robust analysis for genetic architecture of quantitative traits.PMID 18974168Read ↗

Robust Bayesian mapping of quantitative trait loci using Student-t distribution for residual.Semantic proximity Read ↗

A compressed variance component mixed model framework for detecting small and linked QTL-by-environment interactions.Semantic proximity Read ↗

Detection of Epistatic and Gene-Environment Interactions Underlying Three Quality Traits in Rice Using High-Throughput Genome-Wide Data.Semantic proximity Read ↗

Bayesian association mapping of multiple quantitative trait loci and its application to the analysis of genetic variation among Oryza sativa L. germplasms.Semantic proximity Read ↗

Advances in genome-wide association studies of complex traits in rice.Semantic proximity Read ↗

A compressed variance component mixed model for detecting QTNs and QTN-by-environment and QTN-by-QTN interactions in genome-wide association studies.Semantic proximity Read ↗

A novel genome-wide association study method for detecting quantitative trait loci interacting with complex population structures in plant genetics.Semantic proximity Read ↗

Toward understanding genetic mechanisms of complex traits in rice.Semantic proximity Read ↗

Identification of QTL-by-environment interaction by controlling polygenic background effect.Semantic proximity Read ↗

Mapping the genetic architecture of complex traits in experimental populations.Semantic proximity Read ↗

Bayesian mapping of genome-wide epistatic imprinted loci for quantitative traits.Semantic proximity Read ↗

The genetic architecture of quantitative traits.Semantic proximity Read ↗

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