Package index • bregr

Class

Class definition and printing.

breg() stable: Creates a new breg-class object
print.breg stable: Print method for breg object
print(<breg_comparison>): Print method for breg_comparison object

Workflow

Core workflow and pipeline wrapper.

br_pipeline() br_set_y() br_set_x() br_set_x2() br_set_model() br_run() stable: Modeling and analysis pipeline
br_compare_models() experimental: Compare univariate and multivariate models

Accessor

Attributes and data accessors from [breg] objects.

br_get_data() br_get_y() br_get_x() br_get_n_x() br_get_x2() br_get_n_x2() br_get_group_by() br_get_config() br_get_models() br_get_model() br_get_model_names() br_rename_models() br_get_results() stable: Accessor functions for breg objects

Visualization

Visualize results using forest plots and more.

br_show_forest() stable: Show a forest plot for regression results
br_show_forest_circle() experimental: Show a circular forest plot for regression results
br_show_risk_network() stable: Show connected risk network plot
br_show_forest_ggstats() stable: Show a forest plot with ggstats interface
br_show_forest_ggstatsplot() stable: Show a forest plot with ggstatsplot interface
br_show_forest_comparison() experimental: Show forest plot for model comparison

Model Diagnostics and Use

Inspect and visualize models for diagnostic purposes, and enable effective model utilization.

br_diagnose() experimental: Diagnose regression models
br_get_model_stats() experimental: Get model-level statistics in tidy format
br_predict() experimental: Predict method for breg objects
br_show_survival_curves() experimental: Show survival curves based on model scores
br_show_fitted_line() stable: Show fitted regression line with visreg interface
br_show_fitted_line_2d() stable: Show 2d fitted regression line with visreg interface
br_show_residuals() experimental: Show residuals vs fitted plot for regression models
br_show_coxph_diagnostics() experimental: Show Cox proportional hazards model diagnostic plots
br_show_nomogram() experimental: Show nomogram for regression models

Table

Output results in table of different formats.

br_show_table() stable: Show model tidy results in table format
br_show_table_gt() stable: Show regression models with gtsummary interface

SEED Pipeline

Identify cancer prognosis target genes from expression data without control samples. Four-step pipeline: screening, enrichment, Lasso/multivariate/stepwise selection, and risk model construction.

br_seed() experimental: Run the full SEED gene selection pipeline
br_seed_screen() experimental: Screen genes via univariate regression
br_seed_select() experimental: Select genes via Lasso -> multivariate -> stepwise regression
br_seed_model() experimental: Build a risk score model from selected genes

Utility

Helpers for analysis and visualization.

br_avail_methods() br_avail_methods_use_exp() br_avail_method_config() stable: Package availability
polar_init() stable: Init a dot plot in polar system
polar_connect() stable: Connects dots