Filter related individuals from a study — filterRelatedness • pecotmr

Iterative greedy algorithm that removes related individuals exceeding a kinship threshold. First reduces large connected components via graph-based pruning (removing highest-degree nodes), then applies plinkQC::relatednessFilter iteratively until no related pairs remain.

Usage

filterRelatedness(
  relatedness,
  relatednessThreshold = 0.0625,
  analysisType = c("maximizeUnrelated", "maximizeCases"),
  columns = RelatednessColumnsParam(),
  phenoData = NULL,
  phenoCol = "pheno",
  pruning = RelatednessPruningParam(),
  plinkQcArgs = PlinkQcOptions(),
  verbose = FALSE
)

Arguments

relatedness: A data.frame of pairwise relatedness estimates (e.g. KING .kin0 output). Must contain columns for IID1, IID2, and relatedness value.
relatednessThreshold: Kinship threshold above which individuals are considered related (default 0.0625, i.e. 2nd degree).
analysisType: One of "maximizeUnrelated" (default) or "maximizeCases". The latter preserves cases in case-control studies.
columns: Which columns of relatedness hold the pair identifiers and the relatedness measure. Build with RelatednessColumnsParam.
phenoData: A data.frame with columns IID and the column named by phenoCol. Required when analysisType = "maximizeCases".
phenoCol: Column name for the phenotype (default "pheno"). Expected to be binary (1 = case, 0 = control).
pruning: Bounds on the graph pre-pruning and the iterative cleanup. Build with RelatednessPruningParam.
plinkQcArgs: Additional arguments forwarded to plinkQC::relatednessFilter. Build with PlinkQcOptions.
verbose: Logical, print progress messages (default FALSE).

Value

A character vector of individual IDs to exclude.

Examples

rel <- data.frame(IID1 = c("s1", "s2"), IID2 = c("s2", "s3"),
  value = c(0.5, 0.1))
filterRelatedness(rel, relatednessThreshold = 0.2,
  columns = RelatednessColumnsParam(value = "value"))
#> Registered S3 method overwritten by 'igraph':
#>   method   from
#>   plot.sir AMR 
#> [1] "s1"