Single-Iteration Permutation for Large-Scale Biobank Data
This function subsets the sample-by-variable dataframe to the "fixed" ...
This function samples individuals by pairs for permuting phenotype vec...
This function recombines the fixed data and permuted data in the paire...
This function recombines the fixed data and permuted data into a permu...
This function samples indices for permuting phenotype vectors in the b...
This function subsets the sample-by-variable data frame to the permuta...
This function infers relatedness categories in the paired-permutation ...
This function pairs individuals in the paired-permutation function (si...
This function divides the sample-by-variable data frame into males and...
This function checks for uneven numbers of individuals within relatedn...
This function reorders the permuted sample-by-variable data frame to m...
Phenotype-IBD correlation
Phenotype correlation plot
Single-iteration paired permutation for large-scale biobank data with ...
SIP-package internal setup
Single-iteration permutation for large-scale biobank data
A single, phenome-wide permutation of large-scale biobank data. When a large number of phenotypes are analyzed in parallel, a single permutation across all phenotypes followed by genetic association analyses of the permuted data enables estimation of false discovery rates (FDRs) across the phenome. These FDR estimates provide a significance criterion for interpreting genetic associations in a biobank context. For the basic permutation of unrelated samples, this package takes a sample-by-variable file with ID, genotypic covariates, phenotypic covariates, and phenotypes as input. For data with related samples, it also takes a file with sample pair-wise identity-by-descent information. The function outputs a permuted sample-by-variable file ready for genome-wide association analysis. See Annis et al. (2021) <doi:10.21203/rs.3.rs-873449/v1> for details.