'GeneSelectR' - Comprehensive Feature Selection Workflow for Bulk RNAseq Datasets

---

Documentation for package ‘GeneSelectR’ version 1.0.1

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

aggregate_feature_importances	Aggregate Feature Importances
AnnotatedGeneLists-class	AnnotatedGeneLists class
annotate_gene_lists	Convert and Annotate Gene Lists
calculate_mean_cv_scores	Calculate Mean Cross-Validation Scores for Various Feature Selection Methods
calculate_overlap_coefficients	Calculate Overlap and Similarity Coefficients between Feature Lists
calculate_permutation_feature_importance	Calculate Permutation Feature Importance
check_python_modules_available	Check Python Module Availability for Examples
compute_GO_child_term_metrics	Retrieve and Plot the Offspring Nodes of GO Terms
configure_environment	Configure Python Environment for GeneSelectR
create_conda_env	Create a specific Conda environment
create_pipelines	Create Pipelines
create_test_metrics_df	Create a Dataframe of Test Metrics
define_sklearn_modules	Define Python modules and scikit-learn submodules
enable_multiprocess	Enable Multiprocessing in Python Environment
evaluate_test_metrics	Evaluate Test Metrics for a Grid Search Model
GeneList-class	GeneList class
GeneSelectR	Gene Selection and Evaluation with GeneSelectR
get_feature_importances	Get Feature Importances
GO_enrichment_analysis	Perform gene set enrichment analysis using clusterProfiler
import_python_packages	Import Python Libraries
install_python_packages	Install necessary Python packages in a specific Conda environment
perform_grid_search	Perform Grid Search or Random Search for Hyperparameter Tuning
PipelineResults-class	PipelineResults class
pipeline_to_list	Convert Scikit-learn Pipeline to Named List
plot_feature_importance	Plot Feature Importance
plot_metrics	Plot Performance Metrics
plot_overlap_heatmaps	Generate Heatmaps to Visualize Overlap and Similarity Coefficients between Feature Lists
plot_upset	Plot Feature Overlaps Using UpSet Plots
run_simplify_enrichment	Run simplifyGOFromMultipleLists with specified measure and method
set_default_fs_methods	Set Default Feature Selection Methods
set_default_param_grids	Set Default Parameter Grids for Feature Selection
set_reticulate_python	Set RETICULATE_PYTHON for the Current Session
skip_if_no_modules	Check if Python Modules are Available
split_data	Split Data into Training and Test Sets
steps_to_tuples	Convert Steps to Tuples