biostudies-literatureUnknown8(1)Nembot-Simo A<h4>Background</h4>In population association studies, standard methods of statistical inference assume that study subjects are independent samples. In genetic association studies, it is therefore of interest to diagnose undocumented close relationships in nominally unrelated study samples.<h4>Results</h4>We describe the R package CrypticIBDcheck to identify pairs of closely-related subjects based on genetic marker data from single-nucleotide polymorphisms (SNPs). The package is able to accommodate SNPs in linkage disequibrium (LD), without the need to thin the markers so that they are approximately independent in the population. Sample pairs are identified by superposing their estimated identity-by-descent (IBD) coefficients on plots of IBD coefficients for pairs of simulated subjects fromSource code for biology and medicine5https://www.ebi.ac.uk/biostudies/studies/S-EPMC3764977biostudies-literatureCrypticIBDcheck: an R package for checking cryptic relatedness in nominally unrelated individuals.PMC3764977McNeney BNembot-Simo AGraham JfalseCrypticIBDcheck: an R package for checking cryptic relatedness in nominally unrelated individuals.<h4>Background</h4>In population association studies, standard methods of statistical inference assume that study subjects are independent samples. In genetic association studies, it is therefore of interest to diagnose undocumented close relationships in nominally unrelated study samples.<h4>Results</h4>We describe the R package CrypticIBDcheck to identify pairs of closely-related subjects based on genetic marker data from single-nucleotide polymorphisms (SNPs). The package is able to accommodate SNPs in linkage disequibrium (LD), without the need to thin the markers so that they are approximately independent in the population. Sample pairs are identified by superposing their estimated identity-by-descent (IBD) coefficients on plots of IBD coefficients for pairs of simulated subjects from2013-01-01T00:00:00Z2013 Feb2025-04-19T17:09:52.306Z2019-03-27T01:15:38ZS-EPMC37649772338443510.1186/1751-0473-8-5