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bravo

An R package that performs Bayesian iterated screening and/or variable selection for ultra-high dimensional Gaussian linear regression models

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Version

Install

install.packages('bravo')

Monthly Downloads

784

Version

4.1.0

License

GPL-3

Maintainer

Dongjin Li

Last Published

June 9th, 2026

Functions in bravo (4.1.0)

dense_to_sparse_converter

Launch the Sparse Converter Shiny App

Convert numeric genotype matrix to sparse matrix

UNITE: Post-process SVEN Model

Tune SVEN for All Hit Sizes

svenetics_pipeline

Full Multi-Trait GWAS Pipeline

Compute marginal inclusion probabilities from a fitted "sven" object.

Tune SVEN Parameters

FDR using correlation threshold

FDR using window size

Bayesian Iterated Screening (ultra-high, high or low dimensional).

basic.sven.model

Run SVEN with Optimal Parameters

FPR using window size

TPR using window size

FPR using correlation threshold

BWAS: Bayesian GWAS for a Single Trait

TPR using correlation threshold

Estimate SVEN Runtime

parameter_selection

Select Optimal Tuning Parameters

Clean SNP Matrix

create_param_mat

Create Parameter Grid

pipeline_single_trait

Run GWAS for a Single Trait

Launch the SVENETICS Shiny App

Selection of variables with embedded screening using Bayesian methods (SVEN) in Gaussian linear models (ultra-high, high or low dimensional).

Run SVEN Across Parameter Grid

Make predictions from a fitted "sven" object.