A B C D F G H K L M N P R S T V W
| ANOVA | ANOVA |
| as_data_frame | Convert to data.frame |
| as_data_frame-method | Convert to data.frame |
| AUC | Area under ROC |
| autoscale | Autoscale |
| balanced_accuracy | Balanced Accuracy |
| blank_filter | Blank filter |
| blank_filter_hist | plot for blank filter |
| bootstrap | Bootstrap class |
| calculate | Calculate metric |
| calculate-method | Calculate metric |
| chart_plot | chart_plot method |
| chart_plot-method | chart_plot method |
| classical_lsq | Classical Least Squares regression |
| compare_dist | Compare distributions |
| confounders_clsq | Check for confounding factors in ttest |
| confounders_lsq_barchart | barchart of percent change |
| confounders_lsq_boxplot | boxplot of percent change |
| constant_sum_norm | Normalisation to constant sum |
| corr_coef | Correlation Coefficient |
| DatasetExperiment_boxplot | DatasetExperiment boxplot |
| DatasetExperiment_dist | Distribution plot |
| DatasetExperiment_factor_barchart | DatasetExperiment_factor_barchart class |
| DatasetExperiment_heatmap | DatasetExperiment_heatmap class |
| DFA | Discriminant Factor Analysis (DFA) |
| dfa_scores_plot | dfa_scores_plot class |
| dratio_filter | D ratio filter |
| feature_boxplot | Feature boxplots |
| feature_profile | Feature profile class |
| filter_by_name | Filter by name |
| filter_na_count | filter_na_count class |
| filter_smeta | filter_smeta class |
| fisher_exact | fisher_exact class |
| fold_change | fold change class |
| fold_change_int | fold change for interactions class |
| fold_change_plot | fold_change plot |
| forward_selection_byrank | forward selection by rank |
| fs_line | forward_selection_plot |
| glog_opt_plot | glog transform optimisation plot |
| glog_transform | glog transform |
| grid_search_1d | grid_search_1d class |
| gs_line | grid_search_plot |
| HCA | HCA method class |
| hca_dendrogram | hca_dendrogram class |
| HSD | HSD model class |
| HSDEM | HSD model class using estimated marginal means |
| kfoldxcv_grid | kfoldxcv_grid class |
| kfoldxcv_metric | kfoldxcv_metric class |
| kfold_xval | kfold_xval model class |
| knn_impute | knn missing value imputation |
| kw_p_hist | plot histogram of p values |
| kw_rank_sum | kruskal-wallis model class |
| linear_model | linear model class |
| log_transform | log transform |
| mean_centre | mean_centre model class |
| mixed_effect | Mixed Effects model class |
| model_apply | Apply method |
| model_apply-method | Apply method |
| model_predict | Model prediction |
| model_predict-method | Model prediction |
| model_reverse | Reverse preprocessing |
| model_reverse-method | Reverse preprocessing |
| model_train | Train a model |
| model_train-method | Train a model |
| MTBLS79_DatasetExperiment | MTBLS79: Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control |
| mv_boxplot | mv_boxplot class |
| mv_feature_filter | filter features by fraction of missing values |
| mv_feature_filter_hist | plot for missing value sample filter |
| mv_histogram | mv_histogram class |
| mv_sample_filter | Missing value filter (samples) |
| mv_sample_filter_hist | plot for missing value sample filter |
| nroot_transform | nroot transform |
| pairs_filter | Pairs filter |
| pareto_scale | Pareto scaling |
| PCA | PCA model class |
| pca_biplot_plot | pca_biplot_plot class |
| pca_correlation_plot | pca_correlation_plot class |
| pca_dstat_plot | pca_dstat_plot_plot class |
| pca_loadings_plot | pca_loadings_plot class |
| pca_scores_plot | pca_scores_plot class |
| pca_scree_plot | pca_scree_plot_plot class |
| permutation_test | Permutation test class |
| permutation_test_plot | permutation_test_plot class |
| permute_sample_order | permute_sample_order class |
| PLSDA | PLSDA model class |
| plsda_predicted_plot | plsda_predicted_plot class |
| plsda_regcoeff_plot | plsda_regcoeff_plot class |
| plsda_roc_plot | plsda_roc_plot class |
| plsda_scores_plot | plsda_scores_plot class |
| plsda_vip_plot | plsda_vip_plot class |
| PLSR | PLSR model class |
| plsr_cook_dist | plsr_cook_dist class |
| plsr_prediction_plot | plsr_prediction_plot class |
| plsr_qq_plot | plsr_qq_plot class |
| plsr_residual_hist | plsr_residual_hist class |
| pqn_norm | Probabilistic Quotient Normalisation |
| pqn_norm_hist | plot for PQN normalisation |
| prop_na | prop_na model class |
| rsd_filter | rsd filter |
| rsd_filter_hist | plot for rsd filter |
| run | Runs an iterator, applying the chosen model multiple times. |
| run-method | Runs an iterator, applying the chosen model multiple times. |
| r_squared | Coefficient of determination class |
| sb_corr | sbcms |
| split_data | Split data into subsets |
| stratified_split | Stratified sampling |
| structToolbox | structToolbox: Examples of tools built using the Statistics in R Using Class Templates (struct) package |
| SVM | SVM model classifier |
| svm_plot_2d | SVM boundary plot (2d) |
| tSNE | tSNE method class |
| tSNE_scatter | tSNE_scatter class |
| ttest | t-test model class |
| vec_norm | Vector normalisation |
| wilcox_p_hist | plot histogram of p values |
| wilcox_test | Wilcoxon signed rank test method class |