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{
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{
            
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  "author": "Melzer, Nina",
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  "author": "Melzer, Nina",
            
3
  "author_email": "",
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  "author_email": "",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.22000/80",
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  "doi": "10.22000/80",
            
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  "doi_date_published": "2018",
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  "doi_date_published": "2018",
            
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  "doi_publisher": "",
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  "doi_publisher": "",
            
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  "doi_status": "True",
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  "doi_status": "True",
            
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  "extra_authors": [
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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Wittenburg, D\u00f6rte",
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      "extra_author": "Wittenburg, D\u00f6rte",
            
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      "orcid": "0000-0002-3639-2574"
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      "orcid": "0000-0002-3639-2574"
            
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    }
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    }
            
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  ],
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  ],
            
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  "groups": [],
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  "groups": [],
            
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  "id": "394909c9-d31f-4391-86c0-72ac4dcd459a",
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  "id": "394909c9-d31f-4391-86c0-72ac4dcd459a",
            
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  "isopen": false,
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  "isopen": false,
            
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  "license_id": "CC BY 4.0 Attribution",
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  "license_id": "CC BY 4.0 Attribution",
            
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  "license_title": "CC BY 4.0 Attribution",
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  "license_title": "CC BY 4.0 Attribution",
            
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  "metadata_created": "2023-01-12T13:30:35.427118",
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  "metadata_created": "2023-01-12T13:30:35.427118",
            
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  "metadata_modified": "2023-08-04T08:52:51.717923",
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  "metadata_modified": "2023-08-04T09:03:33.062686",
            
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  "name": "rdr-doi-10-22000-80",
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  "name": "rdr-doi-10-22000-80",
            
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  "notes": "Abstract: A simulation study has been conducted to analyse 
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  "notes": "Abstract: A simulation study has been conducted to analyse 
            
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the association between genetic and phenotypic variation in livestock.  
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the association between genetic and phenotypic variation in livestock.  
            
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Following the density and distribution of single nucleotide 
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Following the density and distribution of single nucleotide 
            
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polymorphisms (SNPs) on the Illumina BovineSNP50 chip, 52,773 SNPs 
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polymorphisms (SNPs) on the Illumina BovineSNP50 chip, 52,773 SNPs 
            
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were simulated on the cattle genome of 30 Morgan length. Several 
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were simulated on the cattle genome of 30 Morgan length. Several 
            
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generations of random mating were executed in which random 
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generations of random mating were executed in which random 
            
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recombination events according to the genetic distance between SNPs 
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recombination events according to the genetic distance between SNPs 
            
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and random mutation of SNP alleles were considered. In the most recent 
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and random mutation of SNP alleles were considered. In the most recent 
            
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generations, 50 sires were mated to 20 dams in order to generate 
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generations, 50 sires were mated to 20 dams in order to generate 
            
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multiple half-sib families. The data were split into training 
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multiple half-sib families. The data were split into training 
            
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(n=2,000) and validation/testing set (n=2,000). Twenty-three SNPs were 
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(n=2,000) and validation/testing set (n=2,000). Twenty-three SNPs were 
            
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randomly preselected to be the causative variants, and additive, 
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randomly preselected to be the causative variants, and additive, 
            
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dominance and epistatic effects were simulated. Two different traits 
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dominance and epistatic effects were simulated. Two different traits 
            
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were achieved by adding different residual error terms to the sum of 
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were achieved by adding different residual error terms to the sum of 
            
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genetic effects, such that the total genetic variation contributed 
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genetic effects, such that the total genetic variation contributed 
            
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either 30% or 50% to the phenotypic variation. Then, 5,227 SNPs (every 
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either 30% or 50% to the phenotypic variation. Then, 5,227 SNPs (every 
            
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10-th SNP including the causative variants) were selected. The 
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10-th SNP including the causative variants) were selected. The 
            
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simulation was repeated 100 times. More details can be found in 
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simulation was repeated 100 times. More details can be found in 
            
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Wittenburg et al. (2011) Including non-additive genetic effects in 
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Wittenburg et al. (2011) Including non-additive genetic effects in 
            
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Bayesian methods for the prediction of genetic values based on 
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Bayesian methods for the prediction of genetic values based on 
            
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genome-wide markers. BMC Genetics 12:74, 
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genome-wide markers. BMC Genetics 12:74, 
            
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https://doi.org/10.1186/1471-2156-12-74",
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https://doi.org/10.1186/1471-2156-12-74",
            
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  "num_resources": 0,
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  "num_resources": 0,
            
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  "num_tags": 5,
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  "num_tags": 5,
            
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  "orcid": "0000-0002-9586-1588",
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  "orcid": "0000-0002-9586-1588",
            
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  "organization": {
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2023-01-12T13:30:23.238233",
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    "created": "2023-01-12T13:30:23.238233",
            
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    "description": "RADAR (Research Data Repository) is a 
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    "description": "RADAR (Research Data Repository) is a 
            
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cross-disciplinary repository for archiving and publishing research 
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cross-disciplinary repository for archiving and publishing research 
            
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data from completed scientific studies and projects. The focus is on 
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data from completed scientific studies and projects. The focus is on 
            
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research data from subjects that do not yet have their own 
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research data from subjects that do not yet have their own 
            
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discipline-specific infrastructures for research data management. ",
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discipline-specific infrastructures for research data management. ",
            
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    "id": "013c89a9-383c-4200-8baa-0f78bf1d91f9",
            
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    "image_url": "radar-logo.svg",
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    "image_url": "radar-logo.svg",
            
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    "is_organization": true,
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    "is_organization": true,
            
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    "name": "radar",
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    "name": "radar",
            
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    "state": "active",
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    "state": "active",
            
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    "title": "RADAR",
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    "title": "RADAR",
            
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    "type": "organization"
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    "type": "organization"
            
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  },
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  },
            
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  "owner_org": "013c89a9-383c-4200-8baa-0f78bf1d91f9",
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  "owner_org": "013c89a9-383c-4200-8baa-0f78bf1d91f9",
            
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  "private": false,
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  "private": false,
            
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  "production_year": "2010",
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  "production_year": "2010",
            
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  "publication_year": "2018",
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  "publication_year": "2018",
            
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  "publishers": [
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  "publishers": [
            
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    {
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    {
            
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      "publisher": "Leibniz Institute for Farm Animal Biology (FBN)"
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      "publisher": "Leibniz Institute for Farm Animal Biology (FBN)"
            
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    }
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    }
            
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  ],
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  ],
            
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  "related_identifiers": [
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  "related_identifiers": [
            
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    {
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    {
            
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      "identifier": "10.1002/bimj.201700219",
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      "identifier": "10.1002/bimj.201700219",
            
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      "identifier_type": "DOI",
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      "identifier_type": "DOI",
            
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      "relation_type": "IsSupplementTo"
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      "relation_type": "IsSupplementTo"
            
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  ],
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  "repository_name": "RADAR (Research Data Repository)",
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  "repository_name": "RADAR (Research Data Repository)",
            
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  "resource_type": "Dataset - phenotypic and genetic data",
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  "resource_type": "Dataset - phenotypic and genetic data",
            
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  "resources": [],
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  "resources": [],
            
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  "services_used_list": "",
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  "services_used_list": "",
            
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  "source_metadata_created": "2018",
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  "source_metadata_created": "2018",
            
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  "source_metadata_modified": "",
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  "source_metadata_modified": "",
            
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  "state": "active",
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  "state": "active",
            
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  "subject_areas": [
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    {
            
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      "subject_area_additional": "",
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      "subject_area_additional": "",
            
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      "subject_area_name": "Agriculture"
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      "subject_area_name": "Agriculture"
            
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    },
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    },
            
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    {
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    {
            
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      "subject_area_additional": "",
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      "subject_area_additional": "",
            
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      "subject_area_name": "Biology"
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      "subject_area_name": "Biology"
            
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    },
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    },
            
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    {
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    {
            
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      "subject_area_additional": "Genetics",
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      "subject_area_additional": "Genetics",
            
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      "subject_area_name": "Other"
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      "subject_area_name": "Other"
            
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    },
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    },
            
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    {
            
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      "subject_area_additional": "",
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      "subject_area_additional": "",
            
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      "subject_area_name": "Life Science"
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      "subject_area_name": "Life Science"
            
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    }
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    }
            
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  ],
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  ],
            
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  "tags": [
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  "tags": [
            
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    {
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    {
            
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      "display_name": "SNP",
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      "display_name": "SNP",
            
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      "id": "c9540cd0-ade4-4f17-b346-53f464a95aca",
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      "id": "c9540cd0-ade4-4f17-b346-53f464a95aca",
            
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      "name": "SNP",
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      "name": "SNP",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "dominance",
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      "display_name": "dominance",
            
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      "id": "39bbb28b-b873-49d3-8fda-478f66852fa9",
            
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      "name": "dominance",
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      "name": "dominance",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "epistasis",
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      "display_name": "epistasis",
            
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      "id": "5750aa1a-431d-476d-97d4-1740158ce128",
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      "id": "5750aa1a-431d-476d-97d4-1740158ce128",
            
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      "name": "epistasis",
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      "name": "epistasis",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "genetic variation",
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      "display_name": "genetic variation",
            
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      "id": "12ad04c6-acab-4554-afc1-5441330c572a",
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      "id": "12ad04c6-acab-4554-afc1-5441330c572a",
            
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      "name": "genetic variation",
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      "name": "genetic variation",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "recombination",
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      "display_name": "recombination",
            
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      "id": "30f52613-36f9-44fa-8e3d-c10c466a4408",
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      "id": "30f52613-36f9-44fa-8e3d-c10c466a4408",
            
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      "name": "recombination",
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      "name": "recombination",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    }
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    }
            
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  ],
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  ],
            
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  "title": "Supplementary data to publication \u201can approximate 
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  "title": "Supplementary data to publication \u201can approximate 
            
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bayesian significance test for genomic evaluations\u201d (biom j)",
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bayesian significance test for genomic evaluations\u201d (biom j)",
            
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  "type": "vdataset",
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  "type": "vdataset",
            
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  "url": "https://doi.org/10.22000/80"
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  "url": "https://doi.org/10.22000/80"
            
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}
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}