{
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  "Package": "grmsem",
  "Title": "Genetic-Relationship-Matrix Structural Equation Modelling\n(GRMSEM)",
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  "Authors@R": "c(\nperson(\"Beate\", \"StPourcain\", email = \"Beate.StPourcain@mpi.nl\", comment = c(ORCID = \"0000-0002-4680-3517\"), role = c(\"aut\", \"cre\")),\nperson(\"Alexander\", \"Klassmann\", email = \"alex.klassmann@koeln.de\", role = c(\"ctb\"))\n)",
  "Maintainer": "Beate StPourcain <Beate.StPourcain@mpi.nl>",
  "Description": "Quantitative genetics tool supporting the modelling of\nmultivariate genetic variance structures in quantitative data.\nIt allows fitting different models through multivariate\ngenetic-relationship-matrix (GRM) structural equation modelling\n(SEM) in unrelated individuals, using a maximum likelihood\napproach. Specifically, it combines genome-wide genotyping\ninformation, as captured by GRMs, with twin-research-based SEM\ntechniques, St Pourcain et al. (2017)\n<doi:10.1016/j.biopsych.2017.09.020>, Shapland et al. (2020)\n<doi:10.1101/2020.08.14.251199>.",
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  "BugReports": "https://gitlab.gwdg.de/beate.stpourcain/grmsem/-/issues",
  "Packaged": {
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    "User": "root"
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  "Repository": "https://bstpourcain.r-universe.dev",
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        "Download and installation",
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        "Phenotype file",
        "GREML AE models",
        "Multivariate AE models",
        "Model descriptions",
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        "IPC model",
        "Direct Symmetric model",
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        "Data simulation",
        "DS model",
        "Quad-variate example",
        "GREML versus GRM-SEM",
        "References"
      ],
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      "modified": "2021-01-29 08:20:08",
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