LTFGRS (version 1.0.0)

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

Description

Function that constructs the genetic covariance matrix given a graph around a proband and extracts the threshold information from the graph.

Usage

graph_based_covariance_construction_multi(
  fid,
  pid,
  cur_proband_id,
  cur_family_graph,
  h2_vec,
  genetic_corrmat,
  phen_names,
  add_ind = TRUE
)

Value

list with three elements. The first element is temp_tbl, which contains the id of the current proband, the family ID and the lower and upper thresholds for all phenotypes. The second element, cov, is the covariance matrix of the local graph centred on the current proband. The third element is newOrder, which is the order of ids from pid and phen_names pasted together, such that order can be enforced elsewhere too.

Arguments

fid

Name of column with the family ID

pid

Name of column of personal ID

cur_proband_id

id of proband

cur_family_graph

local graph of current proband

h2_vec

vector of liability scale heritabilities

genetic_corrmat

matrix with genetic correlations between considered phenotypes. Must have same order as h2_vec.

phen_names

Names of the phenotypes, as given in cur_family_graph.

add_ind

whether to add genetic liability of the proband or not. Defaults to true.

Examples

fam <- data.frame(
fam = c(1, 1, 1,1),
id = c("pid", "mom", "dad", "pgf"),
dadcol = c("dad", 0, "pgf", 0),
momcol = c("mom", 0, 0, 0))

thresholds <- data.frame(
  id = c("pid", "mom", "dad", "pgf"),
  lower_1 = c(-Inf, -Inf, 0.8, 0.7),
  upper_1 = c(0.8, 0.8, 0.8, 0.7),
  lower_2 = c(-Inf, 0.3, -Inf, 0.2),
  upper_2 = c(0.3, 0.3, 0.3, 0.2))

graph <- prepare_graph(fam, icol = "id", fcol = "dadcol",
 mcol = "momcol", node_attributes = thresholds)

ntrait <- 2
genetic_corrmat <- matrix(0.2, ncol = ntrait, nrow = ntrait)
diag(genetic_corrmat) <- 1
full_corrmat <- matrix(0.3, ncol = ntrait, nrow = ntrait)
diag(full_corrmat) <- 1
h2_vec <- rep(0.6, ntrait)

graph_based_covariance_construction_multi(fid = "fam",
                                          pid = "id",
                                          cur_proband_id = "pid",
                                          cur_family_graph = graph,
                                          h2_vec = h2_vec,
                                          genetic_corrmat = genetic_corrmat,
                                          phen_names = c("1", "2"))