GENESIS-defunct         Defunct functions in package 'GENESIS'
GENESIS-package         GENetic EStimation and Inference in Structured
                        samples (GENESIS): Statistical methods for
                        analyzing genetic data from samples with
                        population structure and/or relatedness
HapMap_ASW_MXL_KINGmat
                        Matrix of Pairwise Kinship Coefficient
                        Estimates for the combined HapMap ASW and MXL
                        Sample found with the KING-robust estimator
                        from the KING software.
admixMap                admixMap
assocTestAggregate      Aggregate Association Testing
assocTestSingle         Genotype Association Testing with Mixed Models
computeVSIF             Computes variant-specific inflation factors
effectAllele            Return the effect allele for association
                        testing
fitNullModel            Fit a Model Under the Null Hypothesis
jointScoreTest          Perform a joint score test
kin2gds                 Store kinship matrix in GDS
kingToMatrix            Convert KING text output to an R Matrix
makeSparseMatrix        Make a sparse matrix from a dense matrix or a
                        table of pairwise values
pcair                   PC-AiR: Principal Components Analysis in
                        Related Samples
pcairPartition          Partition a sample into an ancestry
                        representative 'unrelated subset' and a
                        'related subset'
pcrelate                PC-Relate: Model-Free Estimation of Recent
                        Genetic Relatedness
pcrelateToMatrix        Creates a Genetic Relationship Matrix (GRM) of
                        Pairwise Kinship Coefficient Estimates from
                        PC-Relate Output
plot.pcair              PC-AiR: Plotting PCs
print.pcair             PC-AiR: Principal Components Analysis in
                        Related Samples
sample_annotation_1KG   Annotation for 1000 genomes Phase 3 samples
varCompCI               Variance Component Confidence Intervals
