Quality Control based on KING-robust kinship estimator. More information can be found at https://www.cog-genomics.org/plink/2.0/distance#king_cutoff.
snp_plinkKINGQC(
plink2.path,
bedfile.in,
bedfile.out = NULL,
thr.king = 2^-3.5,
make.bed = TRUE,
ncores = 1,
extra.options = "",
verbose = TRUE
)Path to the executable of PLINK 2.
Path to the input bedfile.
Path to the output bedfile. Default is created by
appending "_norel" to prefix.in (bedfile.in without extension).
Note that KING kinship coefficients are scaled such that duplicate samples have kinship 0.5, not 1. First-degree relations (parent-child, full siblings) correspond to ~0.25, second-degree relations correspond to ~0.125, etc. It is conventional to use a cutoff of ~0.354 (2^-1.5, the geometric mean of 0.5 and 0.25) to screen for monozygotic twins and duplicate samples, ~0.177 (2^-2.5) to remove first-degree relations as well, and ~0.0884 (2^-3.5, default) to remove second-degree relations as well, etc.
Whether to create new bed/bim/fam files (default). Otherwise, returns a table with coefficients of related pairs.
Number of cores used. Default doesn't use parallelism.
You may use bigstatsr::nb_cores().
Other options to be passed to PLINK2 as a string.
Whether to show PLINK log? Default is TRUE.
See parameter make-bed.
Manichaikul, Ani, Josyf C. Mychaleckyj, Stephen S. Rich, Kathy Daly, Michele Sale, and Wei-Min Chen. "Robust relationship inference in genome-wide association studies." Bioinformatics 26, no. 22 (2010): 2867-2873.
if (FALSE) {
bedfile <- system.file("extdata", "example.bed", package = "bigsnpr")
plink2 <- download_plink2(AVX2 = FALSE)
bedfile2 <- snp_plinkKINGQC(plink2, bedfile,
bedfile.out = tempfile(fileext = ".bed"),
ncores = 2)
df_rel <- snp_plinkKINGQC(plink2, bedfile, make.bed = FALSE, ncores = 2)
str(df_rel)
}