Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "12520"
  #_source: array:26 [
    "id" => "12520"
    "slug" => "estimating-relatedness-between-malaria-parasites"
    "yearMonth" => "2019-08"
    "year" => "2019"
    "title" => "Estimating Relatedness Between Malaria Parasites"
    "description" => "TAYLOR, A.R., JACOB, P., NEAFSEY, D.E. et BUCKEE, C.O. (2019). Estimating Relatedness Between Malaria Parasites. <i>Genetics</i>, 212(4), pp. 1337-1351."
    "authors" => array:4 [
      0 => array:3 [
        "name" => "JACOB Pierre"
        "bid" => "B00795650"
        "slug" => "jacob-pierre"
      ]
      1 => array:1 [
        "name" => "TAYLOR Aimee R"
      ]
      2 => array:1 [
        "name" => "NEAFSEY Daniel E"
      ]
      3 => array:1 [
        "name" => "BUCKEE Caroline O"
      ]
    ]
    "ouvrage" => ""
    "keywords" => array:9 [
      0 => "Plasmodium falciparum "
      1 => "Plasmodium vivax "
      2 => "genetic epidemiology "
      3 => "hidden Markov model "
      4 => "identity-by-descent "
      5 => "identity-by-state "
      6 => "independence model "
      7 => "malaria "
      8 => "relatedness."
    ]
    "updatedAt" => "2021-09-24 10:33:27"
    "publicationUrl" => "https://doi.org/10.1534/genetics.119.302120"
    "publicationInfo" => array:3 [
      "pages" => "1337-1351"
      "volume" => "212"
      "number" => "4"
    ]
    "type" => array:2 [
      "fr" => "Articles"
      "en" => "Journal articles"
    ]
    "support_type" => array:2 [
      "fr" => "Revue scientifique"
      "en" => "Scientific journal"
    ]
    "countries" => array:2 [
      "fr" => "États-Unis"
      "en" => "United States of America"
    ]
    "abstract" => array:2 [
      "fr" => "Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. Therefore, it remains unclear how to compare different studies and which measures to use. Here, we systematically compare measures based on identity-by-state (IBS) and identity-by-descent (IBD) using a globally diverse data set of malaria parasites, Plasmodium falciparum and P. vivax, and provide marker requirements for estimates based on IBD. We formally show that the informativeness of polyallelic markers for relatedness inference is maximized when alleles are equifrequent."
      "en" => "Understanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. Therefore, it remains unclear how to compare different studies and which measures to use. Here, we systematically compare measures based on identity-by-state (IBS) and identity-by-descent (IBD) using a globally diverse data set of malaria parasites, Plasmodium falciparum and P. vivax, and provide marker requirements for estimates based on IBD. We formally show that the informativeness of polyallelic markers for relatedness inference is maximized when alleles are equifrequent."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-11-22T01:21:45.000Z"
    "docTitle" => "Estimating Relatedness Between Malaria Parasites"
    "docSurtitle" => "Journal articles"
    "authorNames" => "<a href="/cv/jacob-pierre">JACOB Pierre</a>, TAYLOR Aimee R, NEAFSEY Daniel E, BUCKEE Caroline O"
    "docDescription" => "<span class="document-property-authors">JACOB Pierre, TAYLOR Aimee R, NEAFSEY Daniel E, BUCKEE Caroline O</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2019</span>"
    "keywordList" => "<a href="#">Plasmodium falciparum </a>, <a href="#">Plasmodium vivax </a>, <a href="#">genetic epidemiology </a>, <a href="#">hidden Markov model </a>, <a href="#">identity-by-descent </a>, <a href="#">identity-by-state </a>, <a href="#">independence model </a>, <a href="#">malaria </a>, <a href="#">relatedness.</a>"
    "docPreview" => "<b>Estimating Relatedness Between Malaria Parasites</b><br><span>2019-08 | Journal articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1534/genetics.119.302120" target="_blank">Estimating Relatedness Between Malaria Parasites</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.957596
  +"parent": null
}