FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2119805873> ?p ?o ?g. }

• W2119805873 abstract "Genomic prediction requires estimation of variances of effects of single nucleotide polymorphisms (SNPs), which is computationally demanding, and uses these variances for prediction. We have developed models with separate estimation of SNP variances, which can be applied infrequently, and genomic prediction, which can be applied routinely. SNP variances were estimated with Bayes Stochastic Search Variable Selection (BSSVS) and BayesC. Genome-enhanced breeding values (GEBV) were estimated with RR-BLUP (ridge regression best linear unbiased prediction), using either variances obtained from BSSVS (BLUP-SSVS) or BayesC (BLUP-C), or assuming equal variances for each SNP. Datasets used to estimate SNP variances comprised (1) all animals, (2) 50% random animals (RAN50), (3) 50% best animals (TOP50), or (4) 50% worst animals (BOT50). Traits analysed were protein yield, udder depth, somatic cell score, interval between first and last insemination, direct longevity, and longevity including information from predictors. BLUP-SSVS and BLUP-C yielded similar GEBV as the equivalent Bayesian models that simultaneously estimated SNP variances. Reliabilities of these GEBV were consistently higher than from RR-BLUP, although only significantly for direct longevity. Across scenarios that used data subsets to estimate GEBV, observed reliabilities were generally higher for TOP50 than for RAN50, and much higher than for BOT50. Reliabilities of TOP50 were higher because the training data contained more ancestors of selection candidates. Using estimated SNP variances based on random or non-random subsets of the data, while using all data to estimate GEBV, did not affect reliabilities of the BLUP models. A convergence criterion of 10−8 instead of 10−10 for BLUP models yielded similar GEBV, while the required number of iterations decreased by 71 to 90%. Including a separate polygenic effect consistently improved reliabilities of the GEBV, but also substantially increased the required number of iterations to reach convergence with RR-BLUP. SNP variances converged faster for BayesC than for BSSVS. Combining Bayesian variable selection models to re-estimate SNP variances and BLUP models that use those SNP variances, yields GEBV that are similar to those from full Bayesian models. Moreover, these combined models yield predictions with higher reliability and less bias than the commonly used RR-BLUP model." @default.
• W2119805873 created "2016-06-24" @default.
• W2119805873 creator A5027741500 @default.
• W2119805873 creator A5036106191 @default.
• W2119805873 creator A5067330053 @default.
• W2119805873 date "2014-09-25" @default.
• W2119805873 modified "2023-10-14" @default.
• W2119805873 title "Genomic prediction of breeding values using previously estimated SNP variances" @default.
• W2119805873 cites W1928998639 @default.
• W2119805873 cites W1969709687 @default.
• W2119805873 cites W1969895570 @default.
• W2119805873 cites W1978208556 @default.
• W2119805873 cites W1986084863 @default.
• W2119805873 cites W1992747978 @default.
• W2119805873 cites W1997751006 @default.
• W2119805873 cites W1999398820 @default.
• W2119805873 cites W2011753368 @default.
• W2119805873 cites W2034846276 @default.
• W2119805873 cites W2044821876 @default.
• W2119805873 cites W2045318100 @default.
• W2119805873 cites W2048635991 @default.
• W2119805873 cites W2067715889 @default.
• W2119805873 cites W2074043148 @default.
• W2119805873 cites W2077668635 @default.
• W2119805873 cites W2106330651 @default.
• W2119805873 cites W2114728057 @default.
• W2119805873 cites W2128343509 @default.
• W2119805873 cites W2132022004 @default.
• W2119805873 cites W2137872210 @default.
• W2119805873 cites W2138345444 @default.
• W2119805873 cites W2153634567 @default.
• W2119805873 cites W2157263348 @default.
• W2119805873 cites W2157313957 @default.
• W2119805873 cites W2161040839 @default.
• W2119805873 cites W2162835401 @default.
• W2119805873 cites W2164345668 @default.
• W2119805873 cites W2168202635 @default.
• W2119805873 doi "https://doi.org/10.1186/s12711-014-0052-x" @default.
• W2119805873 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4176585" @default.
• W2119805873 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25928875" @default.
• W2119805873 hasPublicationYear "2014" @default.
• W2119805873 type Work @default.
• W2119805873 sameAs 2119805873 @default.
• W2119805873 citedByCount "9" @default.
• W2119805873 countsByYear W21198058732015 @default.
• W2119805873 countsByYear W21198058732017 @default.
• W2119805873 countsByYear W21198058732018 @default.
• W2119805873 countsByYear W21198058732019 @default.
• W2119805873 countsByYear W21198058732020 @default.
• W2119805873 countsByYear W21198058732023 @default.
• W2119805873 crossrefType "journal-article" @default.
• W2119805873 hasAuthorship W2119805873A5027741500 @default.
• W2119805873 hasAuthorship W2119805873A5036106191 @default.
• W2119805873 hasAuthorship W2119805873A5067330053 @default.
• W2119805873 hasBestOaLocation W21198058731 @default.
• W2119805873 hasConcept C103545067 @default.
• W2119805873 hasConcept C105795698 @default.
• W2119805873 hasConcept C107673813 @default.
• W2119805873 hasConcept C154945302 @default.
• W2119805873 hasConcept C207201462 @default.
• W2119805873 hasConcept C33923547 @default.
• W2119805873 hasConcept C41008148 @default.
• W2119805873 hasConcept C81917197 @default.
• W2119805873 hasConcept C86803240 @default.
• W2119805873 hasConceptScore W2119805873C103545067 @default.
• W2119805873 hasConceptScore W2119805873C105795698 @default.
• W2119805873 hasConceptScore W2119805873C107673813 @default.
• W2119805873 hasConceptScore W2119805873C154945302 @default.
• W2119805873 hasConceptScore W2119805873C207201462 @default.
• W2119805873 hasConceptScore W2119805873C33923547 @default.
• W2119805873 hasConceptScore W2119805873C41008148 @default.
• W2119805873 hasConceptScore W2119805873C81917197 @default.
• W2119805873 hasConceptScore W2119805873C86803240 @default.
• W2119805873 hasIssue "1" @default.
• W2119805873 hasLocation W21198058731 @default.
• W2119805873 hasLocation W21198058732 @default.
• W2119805873 hasLocation W21198058733 @default.
• W2119805873 hasLocation W21198058734 @default.
• W2119805873 hasLocation W21198058735 @default.
• W2119805873 hasLocation W21198058736 @default.
• W2119805873 hasLocation W21198058737 @default.
• W2119805873 hasLocation W21198058738 @default.
• W2119805873 hasOpenAccess W2119805873 @default.
• W2119805873 hasPrimaryLocation W21198058731 @default.
• W2119805873 hasRelatedWork W1969766666 @default.
• W2119805873 hasRelatedWork W2011691467 @default.
• W2119805873 hasRelatedWork W2085829820 @default.
• W2119805873 hasRelatedWork W2117545158 @default.
• W2119805873 hasRelatedWork W2413822334 @default.
• W2119805873 hasRelatedWork W2425966299 @default.
• W2119805873 hasRelatedWork W2970525079 @default.
• W2119805873 hasRelatedWork W3081314636 @default.
• W2119805873 hasRelatedWork W4312456847 @default.
• W2119805873 hasRelatedWork W2592453568 @default.
• W2119805873 hasVolume "46" @default.
• W2119805873 isParatext "false" @default.
• W2119805873 isRetracted "false" @default.
• W2119805873 magId "2119805873" @default.
• W2119805873 workType "article" @default.