<?xml version="1.0" encoding="UTF-8" ?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-10-14T04:48:25Z</responseDate><request identifier="10.22000/284" metadataPrefix="oai_dc" verb="GetRecord">https://www.radar-service.eu/oai/OAIHandler</request><GetRecord><record><header><identifier>10.22000/284</identifier><datestamp>2023-11-15T14:42:33Z</datestamp></header><metadata><oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/"
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   <dc:identifier>https://dx.doi.org/10.22000/284</dc:identifier>
   <dc:creator>Reinsch, Norbert</dc:creator>
   <dc:creator>Blunk, Inga</dc:creator>
   <dc:title>Generalized gametic relationships - a guide to practical implementation</dc:title>
   <dc:publisher> Leibniz Institute for Farm Animal Biology (FBN), Wilhelm-Stahl-Allee 2, 18196 Dummerstorf, Germany</dc:publisher>
   <dc:date>2021</dc:date>
   <dc:subject>Agriculture</dc:subject>
   <dc:type>dataset</dc:type>
   <dc:subject>software for computing the inverse gametic relationship matrix (source code in Fortran2015) and worked small examples using R and the ASReml package). Large mouse data and pedigree with various example analyses. </dc:subject>
   <dc:subject>Workflow</dc:subject>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
   <dc:description>The guide to practical application of generalized gametic relationships has three main parts. The first is the source code (Fortran2015) of a program for setting up the inverse of a generalized gametic relationship matrix from pedigree data, a detailed program description and example input and output files. In the second part six worked examples are presented, demonstrating in very detail how various mixed models with generalized gametic relationship matrices can be implemented using the ASReml package. Each example is accompanied by R-code to check model details and the correctness of the ASReml implementation. Finally a large mouse data set (about 13,000 observations on body weight, 153 generations) is provided together with details on how it can be analyzed with different gametic models using ASReml.</dc:description>
   <dc:subject>parent-of-origin effects, genomic imprinting, gametic relationship matrix, genomic selection, mixed models</dc:subject>
   <dc:language>eng</dc:language>
   <dc:relation>501100001659</dc:relation>
   <dc:format>application/x-tar</dc:format>
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