Man pages for bravo
Bayesian Screening and Variable Selection
| basic.sven.model | Run SVEN with Optimal Parameters |
| bits | Bayesian Iterated Screening (ultra-high, high or low... |
| 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 genotype matrix to sparse matrix |
| dense_to_sparse_converter | Launch the Sparse Converter Shiny App |
| FDR_corrected | FDR using correlation threshold |
| FDR_WS | FDR using window size |
| FPR_corrected | FPR using correlation threshold |
| FPR_WS | FPR using window size |
| jcidx | Jaccard Index |
| mip.sven | Compute marginal inclusion probabilities from a fitted "sven"... |
| 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... |
| svenetics | Launch the SVENETICS Shiny App |
| svenetics_pipeline | Full Multi-Trait GWAS Pipeline |
| TPR_corrected | TPR using correlation threshold |
| TPR_WS | TPR using window size |
| tune.sven | Tune SVEN Parameters |
| tune.sven.all | Tune SVEN for All Hit Sizes |
| unite.sven | UNITE: Post-process SVEN Model |
