Take a pedigree and turn it into a mitochondrial relatedness matrix

Usage

ped2mit(
  ped,
  max_gen = 25,
  sparse = TRUE,
  verbose = FALSE,
  gc = FALSE,
  flatten_diag = FALSE,
  standardize_colnames = TRUE,
  transpose_method = "tcrossprod",
  keep_ids = NULL,
  adjacency_method = "direct",
  saveable = FALSE,
  resume = FALSE,
  save_rate = 5,
  save_rate_gen = save_rate,
  save_rate_parlist = 1e+05 * save_rate,
  save_path = "checkpoint/",
  compress = TRUE,
  force_symmetric = FALSE,
  ...
)

Arguments

ped: a pedigree dataset. Needs ID, momID, and dadID columns
max_gen: the maximum number of iterations that the adjacency matrix is multiplied to get the relatedness matrix. `Inf` uses as many iterations as there are in the data. Defaults to 25.
sparse: logical. If TRUE, use and return sparse matrices from Matrix package
verbose: logical. If TRUE, print progress through stages of algorithm
gc: logical. If TRUE, do frequent garbage collection via gc to save memory
flatten_diag: logical. If TRUE, overwrite the diagonal of the final relatedness matrix with ones
standardize_colnames: logical. If TRUE, standardize the column names of the pedigree dataset
transpose_method: character. The method to use for computing the transpose. Options are "tcrossprod", "crossprod", "star", or "chunked"
keep_ids: character vector of IDs to retain in the final relatedness matrix. When supplied, only the rows of r2 corresponding to these IDs are used in the tcrossprod, so the result is a length(keep_ids) x length(keep_ids) matrix. All columns of r2 are retained during the multiplication so relatedness values remain correct. IDs not found in the pedigree are silently dropped with a warning.
adjacency_method: character. The method to use for computing the adjacency matrix. Options are "loop", "indexed", direct or beta
saveable: logical. If TRUE, save the intermediate results to disk
resume: logical. If TRUE, resume from a checkpoint
save_rate: numeric. The rate at which to save the intermediate results
save_rate_gen: numeric. The rate at which to save the intermediate results by generation. If NULL, defaults to save_rate
save_rate_parlist: numeric. The rate at which to save the intermediate results by parent list. If NULL, defaults to save_rate*1000
save_path: character. The path to save the checkpoint files
compress: logical. If TRUE, use compression when saving the checkpoint files. Defaults to TRUE.
force_symmetric: logical. If TRUE, force the final relatedness matrix to be symmetric. This can help mitigate any numerical asymmetry introduced by the transpose method, especially when using sparse matrices. Defaults to TRUE.
...: additional arguments to be passed to ped2com

Details

The algorithms and methodologies used in this function are further discussed and exemplified in the vignette titled "examplePedigreeFunctions". For more advanced scenarios and detailed explanations, consult this vignette.