{
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  "Package": "LTFGRS",
  "Type": "Package",
  "Title": "Implementation of Several Phenotype-Based Family Genetic Risk\nScores",
  "Version": "1.1.1",
  "Authors@R": "c(\nperson(\"Emil Michael\", \"Pedersen\", email = \"emp@ph.au.dk\", role = c(\"aut\", \"cre\")),\nperson(\"Jette\", \"Steinbach\", , email = \"jst@econ.au.dk\", role = \"aut\"),\nperson(\"Lucas\", \"Rasmussen\", email = \"lar.ncrr@au.dk\", role = \"ctb\"),\nperson(\"Morten Dybdahl\", \"Krebs\", email = \"morten.dybdahl.krebs@regionh.dk\", role = \"aut\"))",
  "Description": "Implementation of several phenotype-based family genetic\nrisk scores with unified input data and data preparation\nfunctions to help facilitate the required data preparation and\nmanagement. The implemented family genetic risk scores are the\nextended liability threshold model conditional on family\nhistory from Pedersen (2022) <doi:10.1016/j.ajhg.2022.01.009>\nand Pedersen (2023)\n<https://www.nature.com/articles/s41467-023-41210-z>,\nPearson-Aitken Family Genetic Risk Scores from Krebs (2024)\n<doi:10.1016/j.ajhg.2024.09.009>, and family genetic risk score\nfrom Kendler (2021) <doi:10.1001/jamapsychiatry.2021.0336>.",
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  "Repository": "https://emilmip.r-universe.dev",
  "Date/Publication": "2026-03-18 10:17:35 UTC",
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  "Author": "Emil Michael Pedersen [aut, cre],\nJette Steinbach [aut],\nLucas Rasmussen [ctb],\nMorten Dybdahl Krebs [aut]",
  "Maintainer": "Emil Michael Pedersen <emp@ph.au.dk>",
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    "censor_family_onsets",
    "construct_covmat",
    "construct_covmat_multi",
    "construct_covmat_single",
    "convert_age_to_cir",
    "convert_age_to_thresh",
    "convert_cir_to_age",
    "convert_format",
    "convert_liability_to_aoo",
    "convert_observed_to_liability_scale",
    "correct_positive_definite",
    "estimate_gen_liability_ltfh",
    "estimate_liability",
    "estimate_liability_multi",
    "estimate_liability_single",
    "extract_estimation_info_graph",
    "extract_estimation_info_graph_multi",
    "extract_estimation_info_tbl",
    "extract_estimation_info_tbl_multi",
    "familywise_attach_attributes",
    "familywise_censoring",
    "familywise_censoring_multi",
    "get_all_combs",
    "get_covmat",
    "get_family_graphs",
    "get_generations",
    "get_onset_time",
    "get_relatedness",
    "get_relations",
    "Gibbs_estimator",
    "graph_based_covariance_construction",
    "graph_based_covariance_construction_multi",
    "graph_to_trio",
    "kendler_family_calculations",
    "kendler_simplified",
    "label_relatives",
    "PA_algorithm",
    "prepare_graph",
    "prepare_thresholds",
    "prepare_thresholds_multi",
    "Relation_per_proband_plot",
    "rtmvnorm.gibbs",
    "simulate_under_LTM",
    "simulate_under_LTM_multi",
    "simulate_under_LTM_single",
    "tnorm_mean",
    "tnorm_mixture_conditional",
    "tnorm_var",
    "truncated_normal_cdf"
  ],
  "_help": [
    {
      "page": "attach_attributes",
      "title": "Attach attributes to a family graphs",
      "topics": [
        "attach_attributes"
      ]
    },
    {
      "page": "censor_family_onsets",
      "title": "Censor onset times in a family based on a proband's end of follow-up.",
      "topics": [
        "censor_family_onsets"
      ]
    },
    {
      "page": "construct_covmat",
      "title": "Constructing a covariance matrix for a variable number of phenotypes",
      "topics": [
        "construct_covmat"
      ]
    },
    {
      "page": "construct_covmat_multi",
      "title": "Constructing a covariance matrix for multiple phenotypes",
      "topics": [
        "construct_covmat_multi"
      ]
    },
    {
      "page": "construct_covmat_single",
      "title": "Constructing a covariance matrix for a single phenotype",
      "topics": [
        "construct_covmat_single"
      ]
    },
    {
      "page": "convert_age_to_cir",
      "title": "Convert age to cumulative incidence rate",
      "topics": [
        "convert_age_to_cir"
      ]
    },
    {
      "page": "convert_age_to_thresh",
      "title": "Convert age to threshold",
      "topics": [
        "convert_age_to_thresh"
      ]
    },
    {
      "page": "convert_cir_to_age",
      "title": "Convert cumulative incidence rate to age",
      "topics": [
        "convert_cir_to_age"
      ]
    },
    {
      "page": "convert_format",
      "title": "Attempts to convert the list entry input format to a long format",
      "topics": [
        "convert_format"
      ]
    },
    {
      "page": "convert_liability_to_aoo",
      "title": "Convert liability to age of onset",
      "topics": [
        "convert_liability_to_aoo"
      ]
    },
    {
      "page": "convert_observed_to_liability_scale",
      "title": "Convert the heritability on the observed scale to that on the liability scale",
      "topics": [
        "convert_observed_to_liability_scale"
      ]
    },
    {
      "page": "correct_positive_definite",
      "title": "Positive definite matrices",
      "topics": [
        "correct_positive_definite"
      ]
    },
    {
      "page": "estimate_gen_liability_ltfh",
      "title": "Estimate genetic liability similar to LT-FH",
      "topics": [
        "estimate_gen_liability_ltfh"
      ]
    },
    {
      "page": "estimate_liability",
      "title": "Estimating the genetic or full liability for a variable number of phenotypes",
      "topics": [
        "estimate_liability"
      ]
    },
    {
      "page": "estimate_liability_multi",
      "title": "Estimating the genetic or full liability for multiple phenotypes",
      "topics": [
        "estimate_liability_multi"
      ]
    },
    {
      "page": "estimate_liability_single",
      "title": "Estimating the genetic or full liability",
      "topics": [
        "estimate_liability_single"
      ]
    },
    {
      "page": "extract_estimation_info_graph",
      "title": "Title Internal Function used to extact input needed from graph input for liability estimation",
      "topics": [
        "extract_estimation_info_graph"
      ]
    },
    {
      "page": "extract_estimation_info_graph_multi",
      "title": "Title Internal Function used to extact input needed from multi-trait graph input for liability estimation",
      "topics": [
        "extract_estimation_info_graph_multi"
      ]
    },
    {
      "page": "extract_estimation_info_tbl",
      "title": "Title Internal Function used to extact input needed for liability estimation",
      "topics": [
        "extract_estimation_info_tbl"
      ]
    },
    {
      "page": "extract_estimation_info_tbl_multi",
      "title": "Title Internal Function used to extact input needed from multi-trait tibble input for liability estimation",
      "topics": [
        "extract_estimation_info_tbl_multi"
      ]
    },
    {
      "page": "familywise_attach_attributes",
      "title": "Wrapper to attach attributes to family graphs",
      "topics": [
        "familywise_attach_attributes"
      ]
    },
    {
      "page": "familywise_censoring",
      "title": "Censor Family Onsets for Multiple Families",
      "topics": [
        "familywise_censoring"
      ]
    },
    {
      "page": "familywise_censoring_multi",
      "title": "Familywise Censoring for Multiple Outcomes",
      "topics": [
        "familywise_censoring_multi"
      ]
    },
    {
      "page": "fixSexCoding",
      "title": "Fixing sex coding in trio info",
      "topics": [
        "fixSexCoding"
      ]
    },
    {
      "page": "get_all_combs",
      "title": "construct all combinations of input vector",
      "topics": [
        "get_all_combs"
      ]
    },
    {
      "page": "get_covmat",
      "title": "Construct kinship matrix from graph",
      "topics": [
        "get_covmat"
      ]
    },
    {
      "page": "get_family_graphs",
      "title": "Automatically identify family members of degree n",
      "topics": [
        "get_family_graphs"
      ]
    },
    {
      "page": "get_generations",
      "title": "Compute Generational Distances and Kinship Coefficients from a Family Graph",
      "topics": [
        "get_generations"
      ]
    },
    {
      "page": "get_onset_time",
      "title": "Calculate age of diagnosis, age at end of follow up, and status",
      "topics": [
        "get_onset_time"
      ]
    },
    {
      "page": "get_relatedness",
      "title": "Relatedness between a pair of family members",
      "topics": [
        "get_relatedness"
      ]
    },
    {
      "page": "get_relations",
      "title": "Compute and Label Pairwise Relationships Across Multiple Family Graphs",
      "topics": [
        "get_relations"
      ]
    },
    {
      "page": "Gibbs_estimator",
      "title": "Wrapper around the Gibbs Sampler that returns formatted liability estimates for the proband",
      "topics": [
        "Gibbs_estimator"
      ]
    },
    {
      "page": "graph_based_covariance_construction",
      "title": "Constructing covariance matrix from local family graph",
      "topics": [
        "graph_based_covariance_construction"
      ]
    },
    {
      "page": "graph_based_covariance_construction_multi",
      "title": "Constructing covariance matrix from local family graph for multi trait analysis",
      "topics": [
        "graph_based_covariance_construction_multi"
      ]
    },
    {
      "page": "graph_to_trio",
      "title": "Convert from igraph to trio information",
      "topics": [
        "graph_to_trio"
      ]
    },
    {
      "page": "kendler_family_calculations",
      "title": "Title Helper function for Kendler's FGRS",
      "topics": [
        "kendler_family_calculations"
      ]
    },
    {
      "page": "kendler_simplified",
      "title": "(Simplified) Kendler's FGRS",
      "topics": [
        "kendler_simplified"
      ]
    },
    {
      "page": "label_relatives",
      "title": "Label Pairwise Relationships Based on Generational Distance and Kinship Coefficient",
      "topics": [
        "label_relatives"
      ]
    },
    {
      "page": "PA_algorithm",
      "title": "Title Pearson-Aitken algorithm to calculate mean values in truncated multivariate normal distributions",
      "topics": [
        "PA_algorithm"
      ]
    },
    {
      "page": "prepare_graph",
      "title": "Construct graph from register information",
      "topics": [
        "prepare_graph"
      ]
    },
    {
      "page": "prepare_thresholds",
      "title": "Calculate (personalised) thresholds based on CIPs.",
      "topics": [
        "prepare_thresholds"
      ]
    },
    {
      "page": "prepare_thresholds_multi",
      "title": "Prepare thresholds for multiple phenotypes",
      "topics": [
        "prepare_thresholds_multi"
      ]
    },
    {
      "page": "Relation_per_proband_plot",
      "title": "Plot the (Average) Number of Relatives per Proband by Relationship Type",
      "topics": [
        "Relation_per_proband_plot"
      ]
    },
    {
      "page": "rtmvnorm.gibbs",
      "title": "Gibbs Sampler for the truncated multivariate normal distribution",
      "topics": [
        "rtmvnorm.gibbs"
      ]
    },
    {
      "page": "simulate_under_LTM",
      "title": "Simulate under the liability threshold model.",
      "topics": [
        "simulate_under_LTM"
      ]
    },
    {
      "page": "simulate_under_LTM_multi",
      "title": "Simulate under the liability threshold model (multiple phenotypes).",
      "topics": [
        "simulate_under_LTM_multi"
      ]
    },
    {
      "page": "simulate_under_LTM_single",
      "title": "Simulate under the liability threshold model (single phenotype).",
      "topics": [
        "simulate_under_LTM_single"
      ]
    },
    {
      "page": "tnorm_mean",
      "title": "Title: Calculate the mean of the truncated normal distribution",
      "topics": [
        "tnorm_mean"
      ]
    },
    {
      "page": "tnorm_mixture_conditional",
      "title": "Title: Calculates mean and variance of mixture of two truncated normal distributions",
      "topics": [
        "tnorm_mixture_conditional"
      ]
    },
    {
      "page": "tnorm_var",
      "title": "Title: Calculate the variance of the truncated normal distribution",
      "topics": [
        "tnorm_var"
      ]
    },
    {
      "page": "truncated_normal_cdf",
      "title": "CDF for truncated normal distribution.",
      "topics": [
        "truncated_normal_cdf"
      ]
    }
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