Man pages for mirvie/mirmodels
Models Built by the Informatics Team at Mirvie
| autoplot.mirvie_learning_curve | Produce a learning curve plot from a mirvie_learning_curve... |
| autoplot.mirvie_learning_curve_cv | Produce a learning curve plot from a mirvie_learning_curve... |
| compute_pcas | Compute principal components. |
| compute_umap | Compute UMAPs. |
| conv_traintest_lst_to_rsplit | Convert a list of 'training_data' and 'testing_data' to an... |
| cor_de | Conduct a differential expression analysis using correlation... |
| deseq | Conduct a differential expression analysis using... |
| edger | Conduct a differential expression analysis using... |
| learn_curve | Get the learning curve of a model as training data quantity... |
| learn_curve_cv | Create a cross-validation learning curve. |
| linear_correct | Correct data for the effects of selected covariates. |
| multi_aov | Perform multiple analyses of variance on linear model... |
| multi_fitteds | Get the fitted values from multiple linear models. |
| multi_lm | Fit multiple linear models. |
| multi_resids | Get the residuals from multiple linear models. |
| new_mirvie_learning_curve | Construct a 'mirvie_learning_curve' object. |
| new_mirvie_learning_curve_cv | Construct a 'mirvie_learning_curve' object. |
| padj_cutoff | Adjusted p-value cutoff |
| pipe | Pipe operator |
| plot_roc | Plot ROC curves with confidence intervals. |
| qqplot_pvals | QQ-plot a vector of p-values. |
| reexports | Objects exported from other packages |
| step_select_genes | Gene selection by differential expression analysis. |
| summary.mirmodels_multi_aov_df | Summarize the output of 'multi_aov()'. |
| train_gbm | Train a gradient boosted model. |
| train_glm | Train a Generalized Lasso linear model. |
| train_lm | Train a Lasso linear model. |
| train_on_grid | Train several models with different hyperparameters and... |
| use_mirvie_gbm | Set up a GBM. |
| use_mirvie_glm | Set up a GLM. |
| vimp | Get variable importances from a model or list of models. |
