Genotype imputation for genome-wide association studies View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2010-07

AUTHORS

Jonathan Marchini, Bryan Howie

ABSTRACT

In the past few years genome-wide association (GWA) studies have uncovered a large number of convincingly replicated associations for many complex human diseases. Genotype imputation has been used widely in the analysis of GWA studies to boost power, fine-map associations and facilitate the combination of results across studies using meta-analysis. This Review describes the details of several different statistical methods for imputing genotypes, illustrates and discusses the factors that influence imputation performance, and reviews methods that can be used to assess imputation performance and test association at imputed SNPs. More... »

PAGES

499

References to SciGraph publications

  • 2009-10. Bayesian statistical methods for genetic association studies in NATURE REVIEWS GENETICS
  • 2008-12. Missing data imputation and haplotype phase inference for genome-wide association studies in HUMAN GENETICS
  • 2009-12. Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies in BMC GENETICS
  • 2006-09. In silico method for inferring genotypes in pedigrees in NATURE GENETICS
  • 2008-09. Detection of sharing by descent, long-range phasing and haplotype imputation in NATURE GENETICS
  • 2008-12. Meta-analysis of genome-wide association data identifies four new susceptibility loci for colorectal cancer in NATURE GENETICS
  • 2005-11. Efficiency and power in genetic association studies in NATURE GENETICS
  • 2001-10. Haplotype tagging for the identification of common disease genes in NATURE GENETICS
  • 2008-05. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes in NATURE GENETICS
  • 2007-10-18. A second generation human haplotype map of over 3.1 million SNPs in NATURE
  • 2009-07. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci in NATURE GENETICS
  • 2007-07. A new multipoint method for genome-wide association studies by imputation of genotypes in NATURE GENETICS
  • 2008-06. Common variants near MC4R are associated with fat mass, weight and risk of obesity in NATURE GENETICS
  • 2010-05. Meta-analysis and imputation refines the association of 15q25 with smoking quantity in NATURE GENETICS
  • 2008-12. Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci in NATURE GENETICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nrg2796

    DOI

    http://dx.doi.org/10.1038/nrg2796

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1009739594

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/20517342


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Statistics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Biostatistics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genome-Wide Association Study", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genotype", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Models, Genetic", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Polymorphism, Single Nucleotide", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of Oxford", 
              "id": "https://www.grid.ac/institutes/grid.4991.5", 
              "name": [
                "Department of Statistics, University of Oxford, Oxford, UK."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Marchini", 
            "givenName": "Jonathan", 
            "id": "sg:person.014735204720.83", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014735204720.83"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Chicago", 
              "id": "https://www.grid.ac/institutes/grid.170205.1", 
              "name": [
                "Department of Human Genetics, University of Chicago, Chicago, USA."
              ], 
              "type": "Organization"
            }, 
            "familyName": "Howie", 
            "givenName": "Bryan", 
            "id": "sg:person.01202203254.35", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01202203254.35"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1038/ng.249", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003424220", 
              "https://doi.org/10.1038/ng.249"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2009.01.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005049647"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1214/09-sts311", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005775865"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.120", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006325160", 
              "https://doi.org/10.1038/ng.120"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/500808", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007874903"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/gepi.20359", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011882893"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.0030114", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014364350"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/gepi.20045", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015195728"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2156-10-27", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015834532", 
              "https://doi.org/10.1186/1471-2156-10-27"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0006526", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016582018"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1001-233", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017573512", 
              "https://doi.org/10.1038/ng1001-233"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1001-233", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017573512", 
              "https://doi.org/10.1038/ng1001-233"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.401", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018049882", 
              "https://doi.org/10.1038/ng.401"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.401", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018049882", 
              "https://doi.org/10.1038/ng.401"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0003551", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018977153"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/519795", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019061180"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1863", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019326064", 
              "https://doi.org/10.1038/ng1863"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1863", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019326064", 
              "https://doi.org/10.1038/ng1863"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/1467-9868.00254", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020397650"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2615", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021006418", 
              "https://doi.org/10.1038/nrg2615"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg2615", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021006418", 
              "https://doi.org/10.1038/nrg2615"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.104.031799", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021143102"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1534/genetics.104.031799", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021143102"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.572", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022092141", 
              "https://doi.org/10.1038/ng.572"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.572", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022092141", 
              "https://doi.org/10.1038/ng.572"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/hmg/ddn288", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022365148"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp197", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024675201"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.262", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025725602", 
              "https://doi.org/10.1038/ng.262"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.140", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026795787", 
              "https://doi.org/10.1038/ng.140"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2007.09.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026812733"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/319501", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1027413555"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2009.01.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033548087"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2009.11.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038257977"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/503876", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039624779"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1159/000152448", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041243572"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2008.09.007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041531203"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1669", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042975627", 
              "https://doi.org/10.1038/ng1669"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1669", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042975627", 
              "https://doi.org/10.1038/ng1669"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1669", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042975627", 
              "https://doi.org/10.1038/ng1669"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.1000529", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043446290"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ajhg.2007.11.004", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043532200"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00439-008-0568-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043727385", 
              "https://doi.org/10.1007/s00439-008-0568-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00439-008-0568-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043727385", 
              "https://doi.org/10.1007/s00439-008-0568-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00439-008-0568-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043727385", 
              "https://doi.org/10.1007/s00439-008-0568-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.84.8.2363", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044151047"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng.216", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045032711", 
              "https://doi.org/10.1038/ng.216"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.1000279", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046453067"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/gepi.20182", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046509710"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng2088", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046979341", 
              "https://doi.org/10.1038/ng2088"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature06258", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051134045", 
              "https://doi.org/10.1038/nature06258"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.1000508", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051227447"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pgen.1000477", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051911808"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/521987", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052475645"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/gepi.20216", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1053667047"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/381000", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058673096"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/502802", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058783626"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1086/508901", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058786469"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1089/cmb.2007.0133", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059245581"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1109/5.18626", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1061178979"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1142364", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062456030"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1074960373", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1076619967", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/oxfordjournals.molbev.a040269", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1082376739"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2010-07", 
        "datePublishedReg": "2010-07-01", 
        "description": "In the past few years genome-wide association (GWA) studies have uncovered a large number of convincingly replicated associations for many complex human diseases. Genotype imputation has been used widely in the analysis of GWA studies to boost power, fine-map associations and facilitate the combination of results across studies using meta-analysis. This Review describes the details of several different statistical methods for imputing genotypes, illustrates and discusses the factors that influence imputation performance, and reviews methods that can be used to assess imputation performance and test association at imputed SNPs.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1038/nrg2796", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.2757227", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1023607", 
            "issn": [
              "1471-0056", 
              "1471-0064"
            ], 
            "name": "Nature Reviews Genetics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "7", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "11"
          }
        ], 
        "name": "Genotype imputation for genome-wide association studies", 
        "pagination": "499", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "2e660689e19f7c133b7d9aa5946af94fe39c73c251f2dee25dd5ebdfc2801144"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "20517342"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "100962779"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/nrg2796"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1009739594"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/nrg2796", 
          "https://app.dimensions.ai/details/publication/pub.1009739594"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T10:35", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000349_0000000349/records_113667_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://www.nature.com/articles/nrg2796"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/nrg2796'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/nrg2796'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nrg2796'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nrg2796'


     

    This table displays all metadata directly associated to this object as RDF triples.

    273 TRIPLES      21 PREDICATES      87 URIs      26 LITERALS      14 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/nrg2796 schema:about N45be1fd846a94a6e92622dc7fa54b8d9
    2 N7a77f8284cec4cc3a66805ea8c5aac92
    3 N8453f0719ea346d7abad080193dc878f
    4 N9bf16fc10c154b4ab921123ed88f79a3
    5 Ne1aef21d11e84da3862d0767b44e5751
    6 anzsrc-for:01
    7 anzsrc-for:0104
    8 schema:author N8f52712477fc4c6cb8e8545fd2716b7c
    9 schema:citation sg:pub.10.1007/s00439-008-0568-7
    10 sg:pub.10.1038/nature06258
    11 sg:pub.10.1038/ng.120
    12 sg:pub.10.1038/ng.140
    13 sg:pub.10.1038/ng.216
    14 sg:pub.10.1038/ng.249
    15 sg:pub.10.1038/ng.262
    16 sg:pub.10.1038/ng.401
    17 sg:pub.10.1038/ng.572
    18 sg:pub.10.1038/ng1001-233
    19 sg:pub.10.1038/ng1669
    20 sg:pub.10.1038/ng1863
    21 sg:pub.10.1038/ng2088
    22 sg:pub.10.1038/nrg2615
    23 sg:pub.10.1186/1471-2156-10-27
    24 https://app.dimensions.ai/details/publication/pub.1074960373
    25 https://app.dimensions.ai/details/publication/pub.1076619967
    26 https://doi.org/10.1002/gepi.20045
    27 https://doi.org/10.1002/gepi.20182
    28 https://doi.org/10.1002/gepi.20216
    29 https://doi.org/10.1002/gepi.20359
    30 https://doi.org/10.1016/j.ajhg.2007.09.001
    31 https://doi.org/10.1016/j.ajhg.2007.11.004
    32 https://doi.org/10.1016/j.ajhg.2008.09.007
    33 https://doi.org/10.1016/j.ajhg.2009.01.005
    34 https://doi.org/10.1016/j.ajhg.2009.01.013
    35 https://doi.org/10.1016/j.ajhg.2009.11.004
    36 https://doi.org/10.1073/pnas.84.8.2363
    37 https://doi.org/10.1086/319501
    38 https://doi.org/10.1086/381000
    39 https://doi.org/10.1086/500808
    40 https://doi.org/10.1086/502802
    41 https://doi.org/10.1086/503876
    42 https://doi.org/10.1086/508901
    43 https://doi.org/10.1086/519795
    44 https://doi.org/10.1086/521987
    45 https://doi.org/10.1089/cmb.2007.0133
    46 https://doi.org/10.1093/bioinformatics/btp197
    47 https://doi.org/10.1093/hmg/ddn288
    48 https://doi.org/10.1093/oxfordjournals.molbev.a040269
    49 https://doi.org/10.1109/5.18626
    50 https://doi.org/10.1111/1467-9868.00254
    51 https://doi.org/10.1126/science.1142364
    52 https://doi.org/10.1159/000152448
    53 https://doi.org/10.1214/09-sts311
    54 https://doi.org/10.1371/journal.pgen.0030114
    55 https://doi.org/10.1371/journal.pgen.1000279
    56 https://doi.org/10.1371/journal.pgen.1000477
    57 https://doi.org/10.1371/journal.pgen.1000508
    58 https://doi.org/10.1371/journal.pgen.1000529
    59 https://doi.org/10.1371/journal.pone.0003551
    60 https://doi.org/10.1371/journal.pone.0006526
    61 https://doi.org/10.1534/genetics.104.031799
    62 schema:datePublished 2010-07
    63 schema:datePublishedReg 2010-07-01
    64 schema:description In the past few years genome-wide association (GWA) studies have uncovered a large number of convincingly replicated associations for many complex human diseases. Genotype imputation has been used widely in the analysis of GWA studies to boost power, fine-map associations and facilitate the combination of results across studies using meta-analysis. This Review describes the details of several different statistical methods for imputing genotypes, illustrates and discusses the factors that influence imputation performance, and reviews methods that can be used to assess imputation performance and test association at imputed SNPs.
    65 schema:genre research_article
    66 schema:inLanguage en
    67 schema:isAccessibleForFree false
    68 schema:isPartOf N59f8c6c755e8464b8d761f1559b21976
    69 N7663a6e6d49748a6bc430b07d002b30e
    70 sg:journal.1023607
    71 schema:name Genotype imputation for genome-wide association studies
    72 schema:pagination 499
    73 schema:productId N259f2c3f6d2a48babe9eda9c3eb9c4fc
    74 N88906500259c4283bc91c7914e29971b
    75 Nc77d75a6357446a6ade42ca811914dd0
    76 Nd4ea2574f74348ff8b0cdafcf19e870e
    77 Nde73989a47a3443ba13fe85588eecd44
    78 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009739594
    79 https://doi.org/10.1038/nrg2796
    80 schema:sdDatePublished 2019-04-11T10:35
    81 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    82 schema:sdPublisher N6f682cc701554b1fb0caf525e041bf2a
    83 schema:url https://www.nature.com/articles/nrg2796
    84 sgo:license sg:explorer/license/
    85 sgo:sdDataset articles
    86 rdf:type schema:ScholarlyArticle
    87 N21e7cba4d7ed4e3dbcb27b2769f28dc2 rdf:first sg:person.01202203254.35
    88 rdf:rest rdf:nil
    89 N259f2c3f6d2a48babe9eda9c3eb9c4fc schema:name dimensions_id
    90 schema:value pub.1009739594
    91 rdf:type schema:PropertyValue
    92 N45be1fd846a94a6e92622dc7fa54b8d9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    93 schema:name Models, Genetic
    94 rdf:type schema:DefinedTerm
    95 N59f8c6c755e8464b8d761f1559b21976 schema:volumeNumber 11
    96 rdf:type schema:PublicationVolume
    97 N6f682cc701554b1fb0caf525e041bf2a schema:name Springer Nature - SN SciGraph project
    98 rdf:type schema:Organization
    99 N7663a6e6d49748a6bc430b07d002b30e schema:issueNumber 7
    100 rdf:type schema:PublicationIssue
    101 N7a77f8284cec4cc3a66805ea8c5aac92 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    102 schema:name Genome-Wide Association Study
    103 rdf:type schema:DefinedTerm
    104 N8453f0719ea346d7abad080193dc878f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    105 schema:name Biostatistics
    106 rdf:type schema:DefinedTerm
    107 N88906500259c4283bc91c7914e29971b schema:name nlm_unique_id
    108 schema:value 100962779
    109 rdf:type schema:PropertyValue
    110 N8f52712477fc4c6cb8e8545fd2716b7c rdf:first sg:person.014735204720.83
    111 rdf:rest N21e7cba4d7ed4e3dbcb27b2769f28dc2
    112 N9bf16fc10c154b4ab921123ed88f79a3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    113 schema:name Polymorphism, Single Nucleotide
    114 rdf:type schema:DefinedTerm
    115 Nc77d75a6357446a6ade42ca811914dd0 schema:name doi
    116 schema:value 10.1038/nrg2796
    117 rdf:type schema:PropertyValue
    118 Nd4ea2574f74348ff8b0cdafcf19e870e schema:name pubmed_id
    119 schema:value 20517342
    120 rdf:type schema:PropertyValue
    121 Nde73989a47a3443ba13fe85588eecd44 schema:name readcube_id
    122 schema:value 2e660689e19f7c133b7d9aa5946af94fe39c73c251f2dee25dd5ebdfc2801144
    123 rdf:type schema:PropertyValue
    124 Ne1aef21d11e84da3862d0767b44e5751 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    125 schema:name Genotype
    126 rdf:type schema:DefinedTerm
    127 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    128 schema:name Mathematical Sciences
    129 rdf:type schema:DefinedTerm
    130 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
    131 schema:name Statistics
    132 rdf:type schema:DefinedTerm
    133 sg:grant.2757227 http://pending.schema.org/fundedItem sg:pub.10.1038/nrg2796
    134 rdf:type schema:MonetaryGrant
    135 sg:journal.1023607 schema:issn 1471-0056
    136 1471-0064
    137 schema:name Nature Reviews Genetics
    138 rdf:type schema:Periodical
    139 sg:person.01202203254.35 schema:affiliation https://www.grid.ac/institutes/grid.170205.1
    140 schema:familyName Howie
    141 schema:givenName Bryan
    142 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01202203254.35
    143 rdf:type schema:Person
    144 sg:person.014735204720.83 schema:affiliation https://www.grid.ac/institutes/grid.4991.5
    145 schema:familyName Marchini
    146 schema:givenName Jonathan
    147 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014735204720.83
    148 rdf:type schema:Person
    149 sg:pub.10.1007/s00439-008-0568-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043727385
    150 https://doi.org/10.1007/s00439-008-0568-7
    151 rdf:type schema:CreativeWork
    152 sg:pub.10.1038/nature06258 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051134045
    153 https://doi.org/10.1038/nature06258
    154 rdf:type schema:CreativeWork
    155 sg:pub.10.1038/ng.120 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006325160
    156 https://doi.org/10.1038/ng.120
    157 rdf:type schema:CreativeWork
    158 sg:pub.10.1038/ng.140 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026795787
    159 https://doi.org/10.1038/ng.140
    160 rdf:type schema:CreativeWork
    161 sg:pub.10.1038/ng.216 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045032711
    162 https://doi.org/10.1038/ng.216
    163 rdf:type schema:CreativeWork
    164 sg:pub.10.1038/ng.249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003424220
    165 https://doi.org/10.1038/ng.249
    166 rdf:type schema:CreativeWork
    167 sg:pub.10.1038/ng.262 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025725602
    168 https://doi.org/10.1038/ng.262
    169 rdf:type schema:CreativeWork
    170 sg:pub.10.1038/ng.401 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018049882
    171 https://doi.org/10.1038/ng.401
    172 rdf:type schema:CreativeWork
    173 sg:pub.10.1038/ng.572 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022092141
    174 https://doi.org/10.1038/ng.572
    175 rdf:type schema:CreativeWork
    176 sg:pub.10.1038/ng1001-233 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017573512
    177 https://doi.org/10.1038/ng1001-233
    178 rdf:type schema:CreativeWork
    179 sg:pub.10.1038/ng1669 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042975627
    180 https://doi.org/10.1038/ng1669
    181 rdf:type schema:CreativeWork
    182 sg:pub.10.1038/ng1863 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019326064
    183 https://doi.org/10.1038/ng1863
    184 rdf:type schema:CreativeWork
    185 sg:pub.10.1038/ng2088 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046979341
    186 https://doi.org/10.1038/ng2088
    187 rdf:type schema:CreativeWork
    188 sg:pub.10.1038/nrg2615 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021006418
    189 https://doi.org/10.1038/nrg2615
    190 rdf:type schema:CreativeWork
    191 sg:pub.10.1186/1471-2156-10-27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015834532
    192 https://doi.org/10.1186/1471-2156-10-27
    193 rdf:type schema:CreativeWork
    194 https://app.dimensions.ai/details/publication/pub.1074960373 schema:CreativeWork
    195 https://app.dimensions.ai/details/publication/pub.1076619967 schema:CreativeWork
    196 https://doi.org/10.1002/gepi.20045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015195728
    197 rdf:type schema:CreativeWork
    198 https://doi.org/10.1002/gepi.20182 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046509710
    199 rdf:type schema:CreativeWork
    200 https://doi.org/10.1002/gepi.20216 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053667047
    201 rdf:type schema:CreativeWork
    202 https://doi.org/10.1002/gepi.20359 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011882893
    203 rdf:type schema:CreativeWork
    204 https://doi.org/10.1016/j.ajhg.2007.09.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026812733
    205 rdf:type schema:CreativeWork
    206 https://doi.org/10.1016/j.ajhg.2007.11.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043532200
    207 rdf:type schema:CreativeWork
    208 https://doi.org/10.1016/j.ajhg.2008.09.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041531203
    209 rdf:type schema:CreativeWork
    210 https://doi.org/10.1016/j.ajhg.2009.01.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033548087
    211 rdf:type schema:CreativeWork
    212 https://doi.org/10.1016/j.ajhg.2009.01.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005049647
    213 rdf:type schema:CreativeWork
    214 https://doi.org/10.1016/j.ajhg.2009.11.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038257977
    215 rdf:type schema:CreativeWork
    216 https://doi.org/10.1073/pnas.84.8.2363 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044151047
    217 rdf:type schema:CreativeWork
    218 https://doi.org/10.1086/319501 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027413555
    219 rdf:type schema:CreativeWork
    220 https://doi.org/10.1086/381000 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058673096
    221 rdf:type schema:CreativeWork
    222 https://doi.org/10.1086/500808 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007874903
    223 rdf:type schema:CreativeWork
    224 https://doi.org/10.1086/502802 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058783626
    225 rdf:type schema:CreativeWork
    226 https://doi.org/10.1086/503876 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039624779
    227 rdf:type schema:CreativeWork
    228 https://doi.org/10.1086/508901 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058786469
    229 rdf:type schema:CreativeWork
    230 https://doi.org/10.1086/519795 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019061180
    231 rdf:type schema:CreativeWork
    232 https://doi.org/10.1086/521987 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052475645
    233 rdf:type schema:CreativeWork
    234 https://doi.org/10.1089/cmb.2007.0133 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059245581
    235 rdf:type schema:CreativeWork
    236 https://doi.org/10.1093/bioinformatics/btp197 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024675201
    237 rdf:type schema:CreativeWork
    238 https://doi.org/10.1093/hmg/ddn288 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022365148
    239 rdf:type schema:CreativeWork
    240 https://doi.org/10.1093/oxfordjournals.molbev.a040269 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082376739
    241 rdf:type schema:CreativeWork
    242 https://doi.org/10.1109/5.18626 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061178979
    243 rdf:type schema:CreativeWork
    244 https://doi.org/10.1111/1467-9868.00254 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020397650
    245 rdf:type schema:CreativeWork
    246 https://doi.org/10.1126/science.1142364 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062456030
    247 rdf:type schema:CreativeWork
    248 https://doi.org/10.1159/000152448 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041243572
    249 rdf:type schema:CreativeWork
    250 https://doi.org/10.1214/09-sts311 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005775865
    251 rdf:type schema:CreativeWork
    252 https://doi.org/10.1371/journal.pgen.0030114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014364350
    253 rdf:type schema:CreativeWork
    254 https://doi.org/10.1371/journal.pgen.1000279 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046453067
    255 rdf:type schema:CreativeWork
    256 https://doi.org/10.1371/journal.pgen.1000477 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051911808
    257 rdf:type schema:CreativeWork
    258 https://doi.org/10.1371/journal.pgen.1000508 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051227447
    259 rdf:type schema:CreativeWork
    260 https://doi.org/10.1371/journal.pgen.1000529 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043446290
    261 rdf:type schema:CreativeWork
    262 https://doi.org/10.1371/journal.pone.0003551 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018977153
    263 rdf:type schema:CreativeWork
    264 https://doi.org/10.1371/journal.pone.0006526 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016582018
    265 rdf:type schema:CreativeWork
    266 https://doi.org/10.1534/genetics.104.031799 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021143102
    267 rdf:type schema:CreativeWork
    268 https://www.grid.ac/institutes/grid.170205.1 schema:alternateName University of Chicago
    269 schema:name Department of Human Genetics, University of Chicago, Chicago, USA.
    270 rdf:type schema:Organization
    271 https://www.grid.ac/institutes/grid.4991.5 schema:alternateName University of Oxford
    272 schema:name Department of Statistics, University of Oxford, Oxford, UK.
    273 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...