Package index • LTFGRS

Family history estimators

Family history estimators available in the LTFGRS package.

estimate_liability(): Estimating the genetic or full liability for a variable number of phenotypes

estimate_gen_liability_ltfh(): Estimate genetic liability similar to LT-FH

kendler(): Title Kendler's FGRS

Data preparation functions

Functions used to prepare data for the family history estimators.

attach_attributes(): Attach attributes to a family graphs

censor_family_onsets(): Censor onset times in a family based on a proband's end of follow-up.

familywise_censoring(): Censor Family Onsets for Multiple Families

familywise_attach_attributes(): Wrapper to attach attributes to family graphs

get_family_graphs(): Automatically identify family members of degree n

get_onset_time(): Calculate age of diagnosis, age at end of follow up, and status

graph_to_trio(): Convert from igraph to trio information

prepare_thresholds(): Calculate (personalised) thresholds based on CIPs.

prepare_graph(): Construct graph from register information

Simulation functions

Functions used to simulate data for the liability threshold model family history estimators.

construct_covmat(): Constructing a covariance matrix for a variable number of phenotypes

construct_covmat_multi(): Constructing a covariance matrix for multiple phenotypes

construct_covmat_single(): Constructing a covariance matrix for a single phenotype

convert_age_to_cir(): Convert age to cumulative incidence rate

convert_age_to_thresh(): Convert age to threshold

convert_cir_to_age(): Convert cumulative incidence rate to age

convert_liability_to_aoo(): Convert liability to age of onset

estimate_liability_single(): Estimating the genetic or full liability

estimate_liability_multi(): Estimating the genetic or full liability for multiple phenotypes

simulate_under_LTM(): Simulate under the liability threshold model.

simulate_under_LTM_multi(): Simulate under the liability threshold model (multiple phenotypes).

simulate_under_LTM_single(): Simulate under the liability threshold model (single phenotype).

convert_format(): Attempts to convert the list entry input format to a long format

Internal functions and functions used in the estimator functions

The primary functions used in the family history estimators and some helper functions.

convert_observed_to_liability_scale(): Convert the heritability on the observed scale to that on the liability scale

correct_positive_definite(): Positive definite matrices

extract_estimation_info_graph(): Title Internal Function used to extact input needed from graph input for liability estimation

extract_estimation_info_tbl(): Title Internal Function used to extact input needed for liability estimation

fixSexCoding(): Fixing sex coding in trio info

get_all_combs(): construct all combinations of input vector

get_covmat(): Construct kinship matrix from graph

get_relatedness(): Relatedness between a pair of family members

graph_based_covariance_construction(): Constructing covariance matrix from local family graph

graph_based_covariance_construction_multi(): Constructing covariance matrix from local family graph for multi trait analysis

Gibbs_estimator(): Wrapper around the Gibbs Sampler that returns formatted liability estimates for the proband

kendler_family_calculations(): Title Helper function for Kendler's FGRS

PA_algorithm(): Title Pearson-Aitken algorithm to calculate mean values in truncated multivariate normal distributions

rtmvnorm.gibbs(): Gibbs Sampler for the truncated multivariate normal distribution

tnorm_mean(): Title: Calculate the mean of the truncated normal distribution

tnorm_mixture_conditional(): Title: Calculates mean and variance of mixture of two truncated normal distributions

tnorm_var(): Title: Calculate the variance of the truncated normal distribution

truncated_normal_cdf(): CDF for truncated normal distribution.