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

Accounting for overlapping annotations in genomic prediction models of complex traits.

BMC bioinformatics - 6 Sept 2022

Mollandin Fanny, Gilbert Hélène, Croiseau Pascal, Rau Andrea

Abstract excerpt

BACKGROUND: It is now widespread in livestock and plant breeding to use genotyping data to predict phenotypes with genomic prediction models. In parallel, genomic annotations related to a variety of traits are increasing in number and granularity, providing valuable insight into potentially important positions in the genome. The BayesRC model integrates this prior biological information by factorizing the genome...

Read the complete abstract on PubMed

Topics

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

Share to Bayes Theorem
Share to Genomics
Share to Genotype

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Models, Genetic

Share to Multifactorial Inheritance

Share to Phenotype

Share to Polymorphism, Single Nucleotide

Source

Open in PubMed Open full text

Identifiers

PMID: 36068513
DOI: 10.1186/s12859-022-04914-5
PMCID: PMC9446854

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Accounting for overlapping annotations in genomic prediction models of complex traits.PMID 36068513Read ↗

Improving genomic prediction accuracy of complex traits by integrating massive types of functional annotation information.Semantic proximity Read ↗

An evaluation of the predictive performance and mapping power of the BayesR model for genomic prediction.Semantic proximity Read ↗

Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits.Semantic proximity Read ↗

A nested mixture model for genomic prediction using whole-genome SNP genotypes.Semantic proximity Read ↗

Genomic prediction with whole-genome sequence data in intensely selected pig lines.Semantic proximity Read ↗

MultiBLUP: improved SNP-based prediction for complex traits.Semantic proximity Read ↗

Application of Bayesian genomic prediction methods to genome-wide association analyses.Semantic proximity Read ↗

Incorporation of Trait-Specific Genetic Information into Genomic Prediction Models.Semantic proximity Read ↗

Genome-wide fine-mapping identifies pleiotropic and functional variants that predict many traits across global cattle populations.Semantic proximity Read ↗

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.Semantic proximity Read ↗

Improving accuracy of genomic prediction by genetic architecture based priors in a Bayesian model.Semantic proximity Read ↗

Evaluation of heritability partitioning approaches in livestock populations.Semantic proximity Read ↗

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