FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2021001301> ?p ?o ?g. }

• W2021001301 endingPage "4098" @default.
• W2021001301 startingPage "4090" @default.
• W2021001301 abstract "Different methods for genomic evaluation were compared for accuracy and feasibility of evaluation using phenotypic, pedigree, and genomic information for a trait influenced by a maternal effect. A simulated population was constructed that included 15,800 animals in 5 generations. Genotypes from 45,000 SNP were available for 1,500 animals in the last 3 generations. Genotyped animals in the last generation had no phenotypes. Weaning weight data were simulated using an animal model with direct and maternal effects. Additive direct and maternal effects were considered either noncorrelated (formula in text) or negatively correlated (formula in text). Methods of analysis were traditional BLUP, BayesC using phenotypes and ignoring maternal effects (BayesCPR), BayesC using deregressed EBV (BayesCDEBV), and single-step genomic BLUP (ssGBLUP). Whereas BayesCPR can be used when phenotypes of only genotyped animals are available, BayesCDEBV can be used when BLUP EBV of genotyped animals are available, and ssGBLUP is suitable when genotypes, phenotypes, and pedigrees are jointly available. For all genotyped and young genotyped animals, mean accuracies from BayesCPR and BayesCDEBV were lower than accuracies from BLUP for direct and maternal effects. The differences in mean accuracy were greater when genetic correlation was negative. Gains in accuracy were observed when ssGBLUP was compared with BLUP; for the direct (maternal) effect the average gain was 0.01 (0.02) for all genotyped animals and 0.03 (0.02) for young genotyped animals without phenotypes. Similar gains were observed for 0 and negative genetic correlation. Accuracy with BayesCPR was affected by ignoring phenotypes of nongenotyped animals and maternal effect and by not accounting for parent average. Accuracy with BayesCDEBV was affected by approximations needed for deregression, not accounting for parent average, and sequential rather than simultaneous fitting of genomic and nongenomic information. Whereas BayesCDEBV presented a considerable bias, especially for maternal effect, ssGBLUP was unbiased for both effects. The computing time was 1 s for BLUP, 44 s for ssGBLUP, and over 2,000 s for BayesC. Greatest computational efficiency and accuracy of genomic prediction for a maternally affected trait was obtained when information from all nongenotyped but related individuals was included and phenotypes, pedigree, and genotypes were available and considered jointly. Increasing the gain in accuracy of genomic predictions obtained by ssGBLUP over BLUP may require an increase in the number of genotyped animals." @default.
• W2021001301 created "2016-06-24" @default.
• W2021001301 creator A5016736828 @default.
• W2021001301 creator A5037292871 @default.
• W2021001301 creator A5039772840 @default.
• W2021001301 creator A5061338178 @default.
• W2021001301 creator A5063601848 @default.
• W2021001301 creator A5091020121 @default.
• W2021001301 date "2013-09-01" @default.
• W2021001301 modified "2023-10-14" @default.
• W2021001301 title "Prediction accuracy for a simulated maternally affected trait of beef cattle using different genomic evaluation models1" @default.
• W2021001301 cites W1480101028 @default.
• W2021001301 cites W1562470511 @default.
• W2021001301 cites W182071368 @default.
• W2021001301 cites W1980120336 @default.
• W2021001301 cites W1985441663 @default.
• W2021001301 cites W1986836206 @default.
• W2021001301 cites W1996784275 @default.
• W2021001301 cites W2002600206 @default.
• W2021001301 cites W2023673366 @default.
• W2021001301 cites W2036326740 @default.
• W2021001301 cites W2041000916 @default.
• W2021001301 cites W2066745970 @default.
• W2021001301 cites W2067715889 @default.
• W2021001301 cites W2075392090 @default.
• W2021001301 cites W2077197942 @default.
• W2021001301 cites W2081190071 @default.
• W2021001301 cites W2098813910 @default.
• W2021001301 cites W2102811409 @default.
• W2021001301 cites W2110787179 @default.
• W2021001301 cites W2110974472 @default.
• W2021001301 cites W2114143990 @default.
• W2021001301 cites W2114849840 @default.
• W2021001301 cites W2116056560 @default.
• W2021001301 cites W2116201188 @default.
• W2021001301 cites W2117424933 @default.
• W2021001301 cites W2124142797 @default.
• W2021001301 cites W2126946018 @default.
• W2021001301 cites W2127763366 @default.
• W2021001301 cites W2142220815 @default.
• W2021001301 cites W2149385055 @default.
• W2021001301 cites W2153508247 @default.
• W2021001301 cites W2154049740 @default.
• W2021001301 cites W2158376448 @default.
• W2021001301 cites W2160607966 @default.
• W2021001301 cites W2161753744 @default.
• W2021001301 cites W2162384934 @default.
• W2021001301 cites W2162844534 @default.
• W2021001301 cites W2164050502 @default.
• W2021001301 cites W2172258339 @default.
• W2021001301 cites W2395745953 @default.
• W2021001301 doi "https://doi.org/10.2527/jas.2012-5826" @default.
• W2021001301 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23893997" @default.
• W2021001301 hasPublicationYear "2013" @default.
• W2021001301 type Work @default.
• W2021001301 sameAs 2021001301 @default.
• W2021001301 citedByCount "17" @default.
• W2021001301 countsByYear W20210013012014 @default.
• W2021001301 countsByYear W20210013012015 @default.
• W2021001301 countsByYear W20210013012019 @default.
• W2021001301 countsByYear W20210013012020 @default.
• W2021001301 countsByYear W20210013012021 @default.
• W2021001301 countsByYear W20210013012022 @default.
• W2021001301 countsByYear W20210013012023 @default.
• W2021001301 crossrefType "journal-article" @default.
• W2021001301 hasAuthorship W2021001301A5016736828 @default.
• W2021001301 hasAuthorship W2021001301A5037292871 @default.
• W2021001301 hasAuthorship W2021001301A5039772840 @default.
• W2021001301 hasAuthorship W2021001301A5061338178 @default.
• W2021001301 hasAuthorship W2021001301A5063601848 @default.
• W2021001301 hasAuthorship W2021001301A5091020121 @default.
• W2021001301 hasConcept C103545067 @default.
• W2021001301 hasConcept C104317684 @default.
• W2021001301 hasConcept C106934330 @default.
• W2021001301 hasConcept C112672928 @default.
• W2021001301 hasConcept C119857082 @default.
• W2021001301 hasConcept C127716648 @default.
• W2021001301 hasConcept C135763542 @default.
• W2021001301 hasConcept C139275648 @default.
• W2021001301 hasConcept C153209595 @default.
• W2021001301 hasConcept C180838311 @default.
• W2021001301 hasConcept C199360897 @default.
• W2021001301 hasConcept C22593422 @default.
• W2021001301 hasConcept C2779234561 @default.
• W2021001301 hasConcept C2780505807 @default.
• W2021001301 hasConcept C2908647359 @default.
• W2021001301 hasConcept C41008148 @default.
• W2021001301 hasConcept C54355233 @default.
• W2021001301 hasConcept C71924100 @default.
• W2021001301 hasConcept C81917197 @default.
• W2021001301 hasConcept C81941488 @default.
• W2021001301 hasConcept C86803240 @default.
• W2021001301 hasConcept C99454951 @default.
• W2021001301 hasConceptScore W2021001301C103545067 @default.
• W2021001301 hasConceptScore W2021001301C104317684 @default.
• W2021001301 hasConceptScore W2021001301C106934330 @default.
• W2021001301 hasConceptScore W2021001301C112672928 @default.
• W2021001301 hasConceptScore W2021001301C119857082 @default.

• next