Zobrazeno 1 - 10
of 337
pro vyhledávání: '"Ignacy Misztal"'
Publikováno v:
Genetics Selection Evolution, Vol 56, Iss 1, Pp 1-12 (2024)
Abstract Background Single-nucleotide polymorphism (SNP) effects can be backsolved from ssGBLUP genomic estimated breeding values (GEBV) and used for genome-wide association studies (ssGWAS). However, obtaining p-values for those SNP effects relies o
Externí odkaz:
https://doaj.org/article/154ee9f2de39406e99f01032337ec158
Autor:
Mary Kate Hollifield, Ching-Yi Chen, Eric Psota, Justin Holl, Daniela Lourenco, Ignacy Misztal
Publikováno v:
Genetics Selection Evolution, Vol 56, Iss 1, Pp 1-14 (2024)
Abstract Background With the introduction of digital phenotyping and high-throughput data, traits that were previously difficult or impossible to measure directly have become easily accessible, offering the opportunity to enhance the efficiency and r
Externí odkaz:
https://doaj.org/article/00890444d25e4ed1b8bf9fac2c88741d
Publikováno v:
Genetics Selection Evolution, Vol 56, Iss 1, Pp 1-18 (2024)
Abstract Background Validation by data truncation is a common practice in genetic evaluations because of the interest in predicting the genetic merit of a set of young selection candidates. Two of the most used validation methods in genetic evaluatio
Externí odkaz:
https://doaj.org/article/db7d2e82f10347a6bdeb013dc12a5626
Autor:
Ching-Yi Chen, Pieter W. Knap, Adria S. Bhatnagar, Shogo Tsuruta, Daniela Lourenco, Ignacy Misztal, Justin W. Holl
Publikováno v:
Frontiers in Genetics, Vol 15 (2024)
This study aimed to investigate genetic parameters for sow pelvic organ prolapse in purebred and crossbred herds. Pelvic organ prolapse was recorded as normal or prolapsed on the individual sow level across 32 purebred and 8 crossbred farms. In total
Externí odkaz:
https://doaj.org/article/de59e49e997f457084078af4fd1f7e66
Autor:
Sungbong Jang, Roger Ros-Freixedes, John M. Hickey, Ching-Yi Chen, Justin Holl, William O. Herring, Ignacy Misztal, Daniela Lourenco
Publikováno v:
Genetics Selection Evolution, Vol 55, Iss 1, Pp 1-14 (2023)
Abstract Background Whole-genome sequence (WGS) data harbor causative variants that may not be present in standard single nucleotide polymorphism (SNP) chip data. The objective of this study was to investigate the impact of using preselected variants
Externí odkaz:
https://doaj.org/article/28cdcd2260864b89960a349718dc62ee
Publikováno v:
Genetics Selection Evolution, Vol 55, Iss 1, Pp 1-19 (2023)
Abstract Background Identifying true positive variants in genome-wide associations (GWA) depends on several factors, including the number of genotyped individuals. The limited dimensionality of genomic information may give insights into the optimal n
Externí odkaz:
https://doaj.org/article/d0a02229cb6c4abdafdd7765c6a41ffc
Publikováno v:
JDS Communications, Vol 4, Iss 4, Pp 260-264 (2023)
The dairy industry is known for its extensive use of artificial insemination, which has resulted in a population where most animals can be traced back to only a few sires. Due to their relatedness to the population, old influential sires could still
Externí odkaz:
https://doaj.org/article/f68549c213d24e329d902f420813a47e
Publikováno v:
Genetics Selection Evolution, Vol 55, Iss 1, Pp 1-13 (2023)
Abstract Background Reliabilities of best linear unbiased predictions (BLUP) of breeding values are defined as the squared correlation between true and estimated breeding values and are helpful in assessing risk and genetic gain. Reliabilities can be
Externí odkaz:
https://doaj.org/article/b71ed19e12824f9cb64241a641e16149
Publikováno v:
Italian Journal of Animal Science, Vol 21, Iss 1, Pp 673-685 (2022)
Single-step genomic best linear unbiased predictor (ssGBLUP) is a methodology for estimating breeding values jointly for genotyped and non-genotyped animals. Since its development in the early 2010s, ssGBLUP faced challenges like modelling missing pe
Externí odkaz:
https://doaj.org/article/5ef5071aa6444f09b24c6db9034136ed
Publikováno v:
JDS Communications, Vol 3, Iss 5, Pp 343-347 (2022)
Evaluations using single-step genomic BLUP require blending the genomic relationship matrix (G) with a positive definite matrix to ensure nonsingularity for solving the mixed model equations. Many organizations blend G with a proportion of the numera
Externí odkaz:
https://doaj.org/article/75e7b49265e54872959f33aecb016f8a