If you have a vector of data that follows a multivariate normal distribution with a mean determined by a matrix of covariates and a known covariance matrix, this package allows you to generate permutation based resamples of your data. This is useful if you wish to do a permutation based test, as opposed to doing a parametric bootstrap, for instance. The distribution of the generated samples will be identical to the original multivariate normal distribution but will not, in general, be a literal permutation of the original values. This is because the process of estimating the mean from the covariate data reduces the dimensionality of the space in which to perform the permutation. For more detail see Abney M (2015) Permutation Testing in the Presence of Polygenic Variation, Genetic Epidemiology, 39, 249-258, and Abney M et al (2002) Quantitative Trait Homozygosity and Association Mapping and Empirical Genome-wide Significance in Large Complex Pedigrees: Fasting Serum Insulin Levels in the Hutterites, American Journal of Human Genetics, 70, 920-934.
Install this package from CRAN using install.packages("MVNpermute").