Výsledky vyhledávání - "Martin H, Lidauer"

Akademický článek

A computationally efficient algorithm to leverage average information REML for (co)variance component estimation in the genomic era

Autor: Ismo Strandén, Esa A. Mäntysaari, Martin H. Lidauer, Robin Thompson, Hongding Gao

Publikováno v: Genetics Selection Evolution, Vol 56, Iss 1, Pp 1-10 (2024)

Abstract Background Methods for estimating variance components (VC) using restricted maximum likelihood (REML) typically require elements from the inverse of the coefficient matrix of the mixed model equations (MME). As genomic information becomes mo

Externí odkaz: https://doaj.org/article/0986bc48e348498cb5eada06e516a113

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Akademický článek

Invited review: Reliability computation from the animal model era to the single-step genomic model era

Autor: Hafedh Ben Zaabza, Curtis P. Van Tassell, Jeremie Vandenplas, Paul VanRaden, Zengting Liu, Herwin Eding, Stephanie McKay, Katrine Haugaard, Martin H. Lidauer, Esa A. Mäntysaari, Ismo Strandén

Publikováno v: Journal of Dairy Science, Vol 106, Iss 3, Pp 1518-1532 (2023)

ABSTRACT: The calculation of exact reliabilities involving the inversion of mixed model equations poses a heavy computational challenge when the system of equations is large. This has prompted the development of different approximation methods. We gi

Externí odkaz: https://doaj.org/article/0f232815be8747e28f17efd1d7e26098

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Akademický článek

A computationally efficient method for approximating reliabilities in large-scale single-step genomic prediction

Autor: Hongding Gao, Andrei A. Kudinov, Matti Taskinen, Timo J. Pitkänen, Martin H. Lidauer, Esa A. Mäntysaari, Ismo Strandén

Publikováno v: Genetics Selection Evolution, Vol 55, Iss 1, Pp 1-14 (2023)

Abstract Background In this study, computationally efficient methods to approximate the reliabilities of genomic estimated breeding values (GEBV) in a single-step genomic prediction model including a residual polygenic (RPG) effect are described. In

Externí odkaz: https://doaj.org/article/4d29456e682c488aa091ee9dd5f550ff

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A computationally efficient method for approximating reliabilities in large-scale single-step genomic prediction

Autor: Hongding, Gao, Andrei A, Kudinov, Matti, Taskinen, Timo J, Pitkänen, Martin H, Lidauer, Esa A, Mäntysaari, Ismo, Strandén

Publikováno v: Genetics, selection, evolution : GSE. 55(1)

In this study, computationally efficient methods to approximate the reliabilities of genomic estimated breeding values (GEBV) in a single-step genomic prediction model including a residual polygenic (RPG) effect are described. In order to calculate t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::2098cb1691f14db878c2c8541ee2543f
https://pubmed.ncbi.nlm.nih.gov/36604633

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Invited review: Reliability computation from the animal model era to the single-step genomic model era

Publikováno v: Journal of Dairy Science, 106(3), 1518-1532
Journal of Dairy Science 106 (2023) 3

The calculation of exact reliabilities involving the inversion of mixed model equations poses a heavy computational challenge when the system of equations is large. This has prompted the development of different approximation methods. We give an over

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6e3fc1ca48c993d18c729770ff80084
https://pubmed.ncbi.nlm.nih.gov/36567247

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Akademický článek

Employing a Monte Carlo algorithm in Newton-type methods for restricted maximum likelihood estimation of genetic parameters.

Autor: Kaarina Matilainen, Esa A Mäntysaari, Martin H Lidauer, Ismo Strandén, Robin Thompson

Publikováno v: PLoS ONE, Vol 8, Iss 12, p e80821 (2013)

Estimation of variance components by Monte Carlo (MC) expectation maximization (EM) restricted maximum likelihood (REML) is computationally efficient for large data sets and complex linear mixed effects models. However, efficiency may be lost due to

Externí odkaz: https://doaj.org/article/0a35311431c4489c8c1ec8fd9d18e80c

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