| assayData | get assayData |
| assayData-method | get assayData |
| assayData<- | set assayData |
| assayData<--method | set assayData |
| batch_norm | batch normalization |
| bridge | bridge different data sets based on conversion factors |
| column_missing_rate | column missing rate |
| column_missing_rate.default | column missing rate |
| column_missing_rate.Metabolite | column missing rate |
| correlation | correlation of features between two Metabolite objects |
| create_Metabolite | Create a Metabolite object |
| df_plasma | Example data. |
| featureData | get featureData |
| featureData-method | get featureData |
| featureData<- | set featureData |
| featureData<--method | set featureData |
| filter_column_constant | filter columns if values are constant |
| filter_column_constant.default | filter columns if values are constant |
| filter_column_constant.Metabolite | filter columns if values are constant |
| filter_column_missing_rate | filter columns using missing rate |
| filter_column_missing_rate.default | filter columns using missing rate |
| filter_column_missing_rate.Metabolite | filter columns using missing rate |
| filter_row_missing_rate | filter rows using missing rate |
| filter_row_missing_rate.default | filter rows using missing rate |
| filter_row_missing_rate.Metabolite | filter rows using missing rate |
| fit_cox | available regression methods |
| fit_glmer | available regression methods |
| fit_lm | available regression methods |
| fit_lme | available regression methods |
| fit_lmer | available regression methods |
| fit_logistic | available regression methods |
| fit_poisson | available regression methods |
| impute | impute missing values |
| impute.default | impute missing values |
| impute.Metabolite | impute missing values |
| impute_kNN | impute missing values |
| inverse_rank_transform | rank-based inverse normal transformation |
| is_outlier | is outlier |
| load_data | Load metabolite data from three separate files |
| load_excel | Load metabolite data from an excel file |
| merge_data | merge two Metabolite objects |
| Metabolite | The Metabolite class |
| Metabolite-class | The Metabolite class |
| modelling_norm | LOESS normalization |
| nearestQC_norm | nearest QC sample normalization |
| outlier_rate | outlier rate |
| outlier_rate.data.frame | outlier rate |
| outlier_rate.default | outlier rate |
| outlier_rate.Metabolite | outlier rate |
| pareto_scale | pareto scale transformation |
| plot_injection_order | injection order scatterplot |
| plot_Metabolite | plot a Metabolite object |
| plot_PCA | plot PCA |
| plot_ROC | ROC |
| plot_tsne | plot tSNE |
| plot_UMAP | Plot UMAP |
| plot_volcano | volcano plot for regression results |
| QCmatrix_norm | QCmatrix normalization |
| QC_pipeline | quality control pipeline |
| regression | regression analysis |
| regression_each | regression analysis |
| replace_outlier | change outlier values as NA or winsorize |
| replace_outlier.data.frame | change outlier values as NA or winsorize |
| replace_outlier.default | change outlier values as NA or winsorize |
| replace_outlier.Metabolite | change outlier values as NA or winsorize |
| row_missing_rate | row missing rate |
| row_missing_rate.default | row missing rate |
| row_missing_rate.Metabolite | row missing rate |
| RSD | RSD |
| run_PCA | Principal Components Analysis |
| sampleData | get sampleData |
| sampleData-method | get sampleData |
| sampleData<- | set sampleData |
| sampleData<--method | set sampleData |
| save_data | Save metabolite data |
| show-method | Print a Metabolite class object |
| subset | subset a Metabolite object. |
| subset.Metabolite | subset a Metabolite object. |
| transformation | apply transformation to a Metabolite object |
| update_Metabolite | Update a Metabolite object |