نتایج جستجو برای: gblup presented accurate estimations in all traits
تعداد نتایج: 17116795 فیلتر نتایج به سال:
Accuracy of Whole-Genome Prediction Using a Genetic Architecture-Enhanced Variance-Covariance Matrix
Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|G...
the present study is paid to the evaluation of the welfare program of the unemployment insurance in iran. the main purpose which was the main reason for performing this thesis, was the unemployment insurance plan’s challenges in iran such as financial problems of this plan, prolongation of the credit receipt for some insured people, unemployment slow exiting from the unemployment insurance fund...
Reliability of genomic selection (GS) models was tested in an admixed population of Atlantic salmon, originating from crossing of several wild subpopulations. The models included ordinary genomic BLUP models (GBLUP), using genome-wide SNP markers of varying densities (1-220 k), a genomic identity-by-descent model (IBD-GS), using linkage analysis of sparse genome-wide markers, as well as a class...
The missing heritability has been a major problem in the analysis of best linear unbiased prediction (BLUP). We introduced the traditional genome-wide association study (GWAS) into the BLUP to improve the heritability estimation. We analyzed eight pork quality traits of the Berkshire breeds using GWAS and BLUP. GWAS detects the putative quantitative trait loci regions given traits. The single n...
the present study was an attempt to conduct a contrastive analysis between general english (ge) and english for specific purposes (esp) texts in terms of cohesion and cohesive devices. to this end, thirty texts from different esp and ge textbooks were randomly selected. then they were analyzed manually to find the frequency of cohesive devices. cohesive devices include reference, substitution, ...
Empirical experience with genomic selection in dairy cattle suggests that the distribution of the effects of single nucleotide polymorphisms (SNPs) might be far from normality for some traits. An alternative, avoiding the use of arbitrary prior information, is the Bayesian Lasso (BL). Regular BL uses a common variance parameter for residual and SNP effects (BL1Var). We propose here a BL with di...
A single-step method allows genetic evaluation using information of phenotypes, pedigree, and markers from genotyped and nongenotyped individuals simultaneously. This paper compared genomic predictions obtained from a single-step BLUP (SSBLUP) method, a genomic BLUP (GBLUP) method, a selection index blending (SELIND) method, and a traditional pedigree-based method (BLUP) for total number of pig...
abstract: the present study is about prophet ishmael, some parts of his life; his personality in the quran and the bible; and the comparison of the content of these two religious books. compilation of the study has been done with a new perspective and new presentation approach. since prophets have been human beings’ role model and their life has been a perfect example for humanity in all ages,...
The accuracy of genomic estimated breeding values (GEBV) was evaluated for sixteen meat quality traits in a Berkshire population (n = 1,191) that was collected from Dasan breeding farm, Namwon, Korea. The animals were genotyped with the Illumina porcine 62 K single nucleotide polymorphism (SNP) bead chips, in which a set of 36,605 SNPs were available after quality control tests. Two methods wer...
Best linear unbiased prediction (BLUP) has been used to estimate the fixed effects and random effects of complex traits. Traditionally, genomic relationship matrix-based (GRM) and random marker-based BLUP analyses are prevalent to estimate the genetic values of complex traits. We used three methods: GRM-based prediction (G-BLUP), random marker-based prediction using an identity matrix (so-calle...
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