FDR_WS                  FDR using window size
FDR_corrected           FDR using correlation threshold
FPR_WS                  FPR using window size
FPR_corrected           FPR using correlation threshold
TPR_WS                  TPR using window size
TPR_corrected           TPR using correlation threshold
basic.sven.model        Run SVEN with Optimal Parameters
bits                    Bayesian Iterated Screening (ultra-high, high
                        or low dimensional).
bwas                    BWAS: Bayesian GWAS for a Single Trait
calc.runtime            Estimate SVEN Runtime
clean                   Clean SNP Matrix
create_param_mat        Create Parameter Grid
dense2sparse            Convert numeric matrix to sparse matrix
dense_to_sparse_converter
                        Launch the Sparse Converter Shiny App
jcidx                   Jaccard Index
mip.sven                Compute marginal inclusion probabilities from a
                        fitted "sven" object.
parameter_selection     Select Optimal Tuning Parameters
pipeline_single_trait   Run GWAS for a Single Trait
predict.sven            Make predictions from a fitted "sven" object.
run_all_params          Run SVEN Across Parameter Grid
sven                    Selection of variables with embedded screening
                        using Bayesian methods (SVEN) in Gaussian
                        linear models (ultra-high, high or low
                        dimensional).
svenetics               Launch the SVENETICS Shiny App
svenetics_pipeline      Full Multi-Trait GWAS Pipeline
tune.sven               Tune SVEN Parameters
tune.sven.all           Tune SVEN for All Hit Sizes
unite.sven              UNITE: Post-process SVEN Model
