Constructing covariance matrix from local family graph — graph_based_covariance

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(
  pid,
  cur_proband_id,
  cur_family_graph,
  h2,
  add_ind = TRUE
)

Arguments

pid: Name of column of personal ID
cur_proband_id: id of proband
cur_family_graph: local graph of current proband
h2: liability scale heritability
add_ind: whether to add genetic liability of the proband or not. Defaults to true.

Value

list with two elements. The first element is temp_tbl, which contains the id of the current proband, the family ID and the lower and upper thresholds. The second element, cov, is the covariance matrix of the local graph centered on the current proband.

Examples

fam <- data.frame(
  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 = c(-Inf, -Inf, 0.8, 0.7),
  upper = c(0.8, 0.8, 0.8, 0.7))

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

graph_based_covariance_construction(pid = "id",
                                    cur_proband_id = "pid",
                                    cur_family_graph = graph,
                                    h2 = 0.5)
#> $temp_tbl
#> # A tibble: 5 × 3
#>   id     lower upper
#>   <chr>  <dbl> <dbl>
#> 1 pid_g -Inf   Inf  
#> 2 pid   -Inf     0.8
#> 3 mom   -Inf     0.8
#> 4 dad      0.8   0.8
#> 5 pgf      0.7   0.7
#> 
#> $covmat
#>       pid_g   pid  mom  dad   pgf
#> pid_g 0.500 0.500 0.25 0.25 0.125
#> pid   0.500 1.000 0.25 0.25 0.125
#> mom   0.250 0.250 1.00 0.00 0.000
#> dad   0.250 0.250 0.00 1.00 0.250
#> pgf   0.125 0.125 0.00 0.25 1.000
#>