Package index • MNet

All functions

DM(): Fold change, p value and vip of the data

ML_Boruta(): Feature selection using Boruta

ML_RF(): Feature selection using random forest

ML_alpha(): Feature selection using lasso or elastic network

ML_logistic(): Feature selection using logistic regression

ML_xgboost(): Feature selection using XGBoost

MetCox(): The cox analysis about the metabolites

ePDAlyser(): Differential abundance (DA) score

ePEAlyser(): KEGG pathway analysis

eSEAlyser(): The eSEAlyser

keggid2pathway(): The kegg pathway corresponding to kegg id

meta_impute(): Impute the NA in data

mlimma(): Differential Metabolite analysis by limma

mnetapp(): MNet shiny app start function.

myscale(): Scale the data

name2keggid(): Change the compound name to kegg id

name2pathway(): seek the metabolits' pathway

name2refmet(): change the compound name to refmet name

pCliTS(): The clinical's time series analysis

pESEA(): The visualization of ESEA in a pathway

pHeatmap(): Heatmap of differential metabolites

pNetCor(): The correlation network's extraction

pPCA(): Plot the PCA (Principal Component Analysis)

pPathview(): the pathview of differential metabolites

pVolcano(): Plot the volcano figure

pZscore(): Visualization of the z-score plot

pathway2pathwayid(): Change the pathway name to pathway id

pathwayinfo(): The gene and the metabolite in the pathway

sNETlyser(): The subnetwork's extraction

survCli(): The survival analysis and visualization

survMet(): The metabolites' survival analysis and visualization

xEnrichViewer(): Function to view enrichment results

xEnricher(): Function to conduct enrichment analysis given the input data and the ontology and its annotation

xEnricherYours(): Function to conduct enrichment analysis given YOUR own input data

xgr(): pathway analysis and visualization