br_seed(), br_seed_screen(),
br_seed_select(), and br_seed_model()
implementing the SEED (Selection of Essential prognostic genes from
Expression Data) pipeline for identifying cancer prognosis target genes
without control samples (#57). Based on Yang et al. (2025) Cancer
Letters, DOI: 10.1016/j.canlet.2025.217960. The four-step pipeline
includes:
br_seed_screen): Univariate screening via
Cox/logistic regression or Spearman correlation against one or more
clinical indicators, with p-value threshold filtering and significance
intersection across indicators.enrich
argument).br_seed_select): Sequential gene selection
through Lasso regularization (glmnet), multivariate regression, and
stepwise selection with reproducibility via seed.br_seed_model): Risk score model construction
with coefficient extraction and optional z-score expression scaling. All
functions return S3 list objects with cli-based print methods, reuse the
existing br_pipeline() engine for batch regression, and
support mirai parallelization via n_workers.br_get_model_stats() returning a tidy data.frame
of per-model summary statistics (N, events, C-index, AIC, LR test p, PH
test p for Cox; N, AIC, deviance for GLM; N, R-squared for LM),
eliminating the need for manual supplementary model fitting to obtain
diagnostic metrics (#68).br_diagnose().FGFR3::TACC3, EGFR-AS1,
1p/2q, gene name, R reserved
words (if, TRUE, NA), and
backtick-quoted user input in x, x2, and
y variables (#69). Refactored repair_names()
with remove_backticks() for robust quoting, and applied
quoting to response variables in br_set_y().biocViews field to DESCRIPTION for Bioconductor
Suggests compatibility.br_compare_models() and
br_show_forest_comparison() (#54).qs with
qs2.br_show_fitted_line() and
br_show_fitted_line_2d() documentation for compatibility
with visreg 3.0, which removes the gg
argument and renames line.par, fill.par,
points.par to line, fill,
points (#65).devtools::check(env_vars = c('_R_CHECK_DEPENDS_ONLY_' = "true"))
and fixed reported check issues.br_pipeline() to reduce running
time.br_show_coxph_diagnostics().Enhancements & New Features:
br_show_forest_circle()for circular forest
plots.br_show_coxph_diagnostics().br_show_nomogram()for clinical prediction
modeling.dry_runoption to br_pipeline()for
pipeline validation.Fixes & Improvements:
br_show_nomogram().br_show_residuals() to show residuals vs fitted
plot for regression models.br_set_x() and br_set_x2() to
properly handle different input types, including valid column names (in
R), invalid column names, and model formula terms.br_get_model_names() and
br_rename_models() to get and set model names.run_parallel in
br_run().br_get_model() by merging it with
br_get_models().options().exponentiate option appropriately in
br_run().br_avail_methods_use_exp() to include
c("poisson", "quasipoisson").log_first option to
br_show_forest().: for interaction term
combinations throughout the package.br_show_forest().br_get_model() couldn’t
properly process multiple string inputs for the idx
parameter.