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Multitrait Bayesian shrinkage and variable selection models with the BGLR-R package

Genetics(2022)10.1093/genetics/iyac112Source: DataRank Database

Multitrait Bayesian shrinkage and variable selection models with the BGLR-R package is a research paper published in Genetics (2022). On theSindex it has a DataRank of 0. It has been cited 79 times.

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Open Access79 citations

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Enrichment:Funding (4 grants)Impact (FWCI 12.61)OA: hybridTopics (50)Linked Datasets (18)DataCite Reuse (18)IDs (PubMed, PMC, OpenAlex)

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Findable (2/2)

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Accessible (1/2)

Open Access

Interoperable (2/2)

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Reusable (0/3)

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Authors (2)

Gustavo de los Campos ORCID,Paulino Pérez‐Rodríguez ORCID

Live enrichment

PubMed:35924977 PMC:PMC9434216 OpenAlex:https://openalex.org/W4289845640

NIH

Grant: GM R01 101219

National Institutes of Health

Grant: 5R01GM101219-06

Statistical Tools for Whole-Genome Analysis & Prediction of Complex Traits and Diseases

Wellcome Trust

Grant: unidentified

unidentified

Michigan State University

FWCI

12.61

Citation Percentile

1.0%

Citation Trend

2022

2023

2024

2025

2026

hybridLicense: cc-by-nc-nd

journalhttps://academic.oup.com/genetics/article-pdf/222/1/iyac112/45616853/iyac112.pdf

publisherhttps://academic.oup.com/genetics/article-pdf/222/1/iyac112/45616853/iyac112.pdf

publisherhttps://academic.oup.com/genetics/advance-article-pdf/doi/10.1093/genetics/iyac112/45317773/iyac112.pdf

journalhttps://doi.org/10.1093/genetics/iyac112

repositoryhttps://pubmed.ncbi.nlm.nih.gov/35924977

Fields of Study

Genetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and AnimalsGenetics and Plant Breeding0301 basic medicine0303 health sciences03 medical and health sciencesAlgorithmsBayes TheoremGenomeGenomicsGenotypeModels, Genetic

MeSH Terms

AlgorithmsBayes TheoremGenotypeModels, GeneticGenomeGenomics

Keywords

Computer scienceSoftwareBenchmark (surveying)Prior probabilityBayesian probabilityGibbs samplingR packageMultivariate statisticsSet (abstract data type)Selection (genetic algorithm)Data miningStatisticsMachine learningArtificial intelligenceMathematicsProgramming languageBayesianHigh-dimensional RegressionGenpredGenomic PredictionShared Data ResourceMultitrait ModelsMultivariate ModelsGenomic RegressionsPedigree RegressionsInvestigationGenomeGenotypeModels, GeneticBayes TheoremGenomicsAlgorithms

Additional file 3 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694051.v1figshare

Additional file 3 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694051figshare

Additional file 4 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694054.v1figshare

Additional file 4 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694054figshare

Additional file 6 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694060.v1figshare

Additional file 6 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694060figshare

Additional file 1 of Revisiting superiority and stability metrics of cultivar performances using genomic data: derivations of new estimators

10.6084/m9.figshare.26730268.v1figshare

Additional file 1 of Revisiting superiority and stability metrics of cultivar performances using genomic data: derivations of new estimators

10.6084/m9.figshare.26730268figshare

Additional file 7 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694063.v1figshare

Additional file 8 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694066figshare

Additional file 7 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694063figshare

Additional file 8 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694066.v1figshare

Additional file 5 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694057.v1figshare

Additional file 5 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.26694057figshare

Additional file 1 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.25422374figshare

Additional file 1 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.25422374.v1figshare

Additional file 2 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.25422422.v1figshare

Additional file 2 of Including microbiome information in a multi-trait genomic evaluation: a case study on longitudinal growth performance in beef cattle

10.6084/m9.figshare.25422422figshare