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Find Leaf Nodes in a Pedigree

Source: R/trimPedigree.R
findLeaves.Rd

Identifies individuals who are structural "leaves" in the pedigree network — those who can potentially be removed without substantially altering the connectivity of the larger tree.

Usage

findLeaves(
  ped,
  personID = "ID",
  momID = "momID",
  dadID = "dadID",
  include_terminal = TRUE,
  include_founder_singletons = TRUE,
  keep_var = NULL,
  keep_vals = NULL,
  verbose = FALSE
)

Arguments

ped

a pedigree dataset. Needs ID, momID, and dadID columns

personID

character. Name of the column in ped for the person ID variable

momID

character. Name of the column in ped for the mother ID variable

dadID

character. Name of the column in ped for the father ID variable

include_terminal

Logical. If TRUE (default), flag individuals with no children (outdegree 0) as leaves.

include_founder_singletons

Logical. If TRUE (default), also flag founders with exactly one child (indegree 0, outdegree 1) as leaves.

keep_var

Character. Optional column name of a phenotypic variable. When supplied, individuals are protected from removal based on their value in this column (see keep_vals).

keep_vals

Optional vector of values in keep_var that protect an individual from being flagged as a leaf. If NULL (default) and keep_var is supplied, any individual with a non-missing value is protected. To protect individuals with missing data instead, pass keep_vals = NA.

verbose

Logical. If TRUE, print counts of each leaf type.

Value

A character vector of person IDs that are leaf nodes.

Details

Two types of leaves are identified:

  • Terminal nodes: individuals with outdegree 0, meaning they have no children recorded in the pedigree. Controlled by include_terminal.

  • Founder singletons: individuals with indegree 0 and outdegree 1, meaning they are founders (no recorded parents) who appear as a parent of exactly one child. Controlled by include_founder_singletons.

In the directed pedigree graph used by ped2graph, edges run from parent to child. Consequently, indegree reflects the number of recorded parents and outdegree reflects the number of recorded children.

See also

trimPedigree to iteratively remove the identified leaves.

Examples

if (FALSE) { # \dontrun{
ped <- data.frame(
  ID    = 1:6,
  dadID = c(NA, NA, 1, 1, 3, NA),
  momID = c(NA, NA, 2, 2, 4, NA)
)
findLeaves(ped)
} # }