activate | Activate Dataset |
addGrps | Add Groups |
addSamples | Add Samples |
adiv | Alpha Diversity Calculation |
agglomTaxa | Agglomerate taxa into parent taxa |
ASVtoTaxa | Translate ASV Numbers to Taxa Names |
autonametoggle | Automatically Name Results |
bdiv | Beta Diversity Analysis |
calcUniVar | Core Univariate Analysis Function |
capitalize | Capitalize a Single-Word String |
changeFactor | Switch to a Different Factor |
changerank | Change the active rank of a dataset |
checkColors | Check Colors of Groups in a Dataset |
checkFormula | Check that a formula is valid for a dataset |
checkGroups | Check that each group has at least a certain number of... |
chooseFactors | Choose Factors for the Dataset |
chooseGrps | Choose Groups to be Analyzed in Each Factor |
chooseSamples | Select specific samples to analyze |
cleanASVs | Clean ASVs in ASV Dataframe |
cleanData | Clean up a metadata factor column in a merged data table |
cleanGroups | Clean Metadata Factors |
cleanUnkTaxa | Rename Taxa with NA and at Species Level |
clearFeatureFilt | Clear Feature Filtering |
clearNormalization | Clear Normalization |
clearProcessing | Clear Normalization and Feature Filtering |
clr | Centered log-ratio functions |
clusterSamples | Cluster samples |
colorGrps | Color Groups |
combineDupeASVs | Combine Identical ASVs |
cor2cov | Convert a symmetric correlation matrix to a covariance matrix... |
countFeatures | Get Number of Included Samples in a Dataset |
countSamples | Get Number of Included Samples in a Dataset |
countSamples.base | Core function for calculating sample sizes |
excludeFeatures | Exclude specific features at a specified taxonomic rank. Only... |
filterLowAbun | Filter Low Abundance Features |
filterLowPrev | Filter Low Prevalence Features |
filterLowRelAbun | Filter Low Relative Abundance Features |
filterLowTotAbun | Filter Low Total Abundance Features |
filterLowVar | Filter Low Variance Features |
filterNAs | Filter Unassigned Taxa |
findSigFisher | Run Fisher Test on Features |
foldChange | Calculate Fold Change |
ftcor | Compute feature correlation matrices for each group and all... |
ftRatio | Calculate ratio between two features |
ftRatiostab | Generate a table of feature ratios |
getdata | Get Data with/without Attached Metadata |
getDiscriminatingFeatures | Get features that uniquely identify one group from other... |
getFeatures | Get list of features in a dataset |
getFormulaVars | Extract Variables from a Formula |
getFtStats | Get Feature Statistics for Filtering |
getLowestRank | Get Lowest Rank in a Dataset |
getNetwork | Get the co-occurence network for a dataset |
getParentTaxa | Get parent taxa |
getRanks | Get All Ranks of a Dataset |
getSamples | Get samples with certain metadata characteristics from a... |
ggcorrplot | Visualization of a correlation matrix using ggplot2 |
glog | Generalized Log |
keepSigFisher | Function for setting whether or not to run Fisher tests to... |
listsigs | List Significant Features of a Dataset in Current State |
listUniques | List features uniquely over/under-expressed in a specified... |
loadFxnlFile | Load pathways file |
loadMDFile | Load metadata file |
loadTaxaFile | Load Taxonomy File |
makeAldex | Make an ALDEx2 CLR Object |
makeASVtab | Make ASV Table |
makeDeseq | Make a DESeq object from a MicroVis dataset |
makePS | Make a phyloseq object from a MicroVis dataset |
makeRankTabs | Make Abundance Tables at Each Rank |
makeTaxMap | Make a taxmap object from a MicroVis dataset |
multisave | Determine how to save multiple figures |
mvaldex | ALDEx2 Differential Abundance Analysis |
mvCClasso | CClasso Network Analysis |
mvcombine | Merge Two Datasets with Different Sample Sets |
mvdeseq | DESeq2 Analysis |
mvdist | Distance Calculation |
mvhelp | List available functions |
mvlefse | LEfSe Analysis |
mvLMEM | Linear Mixed Effects Model Discriminant Analysis |
mvload | MicroVis Data Loading |
mvmelt | Melt the metadata and abundance table at a given rank for the... |
mvmerge | Merge Two Datasets with Overlapping Samples |
mvNetwork | Construct an association network between features |
mvsave | Save Dataset in its Current State |
mvstratify | Make a melted data table grouped by strata |
mvunifrac | Unifrac Distance Calculation |
nameAnalysis | Automatically name the analysis based on factors and the... |
nameStratification | Standardized naming of the stratification of an analysis |
networkClusters | Get feature clusters determined by network analysis |
normalizer | Normalizing Function |
normalizeTable | Normalize a Standalone Abundance Table |
norm_to_total | Total Sum Normalize |
orderGroups | Order Groups |
pairedCor | Correlate abundance of features between paired samples |
parseStratifiers | Parse Stratifiers |
phyloDiversity | Faith's Phylogenetic Diversity Index |
pipe | Pipe operator |
plotAlphaDiv | Plot Alpha Diversity |
plotBetaDiv | Plot Beta Diversity |
plotClad | Plot Cladogram |
plotDeseq | Plot DESeq Results |
plotFeatureDensity | Plot distribution curves of abundances of each feature across... |
plotFtCorlines | Plot correlation trendlines between different features |
plotFtCormat | Plot feature correlation matrix |
plotGroupedBars | Plot grouped bar plot of significant taxa at each rank of all... |
plotHeatmap | Plot Heatmap of Data |
plotHeatTree | Plot Heat Tree |
plotLEFSE | Plot LEfSe analysis (not cladogram plot) |
plotLMEM | Plot Volcano Plots of LMEM Log2FC Results |
plotNetwork | Plot Feature Network |
plotPairedCor | Correlate abundance of features between paired samples |
plotRareCurves | Plot rarefaction curves |
plotRFImp | Plot random forest important features |
plotSampleDensity | Plot distribution curves of feature abundances in each sample |
plotSimilarity | Plot similarity matrix between samples |
plotStackedBars | Plot stacked abundace barplots |
plotUnivar | Plot box-plots of univariate analysis |
pnova | PERMANOVA Analysis |
poolGroups | Pool groups of a factor into fewer, larger groups |
posthoctoggle | Switch between Tukey/Games-Howell or T-test/Wilcox for... |
print.mvdata | Print function for mvdata (MicroVis dataset) objects |
print.mvmerged | Print function for mvmerged (merged MicroVis dataset) objects |
processDataset | Process Dataset for Analysis |
pval.sparccboot | SparCC p-vals |
rangetotext | Translate Range Factor Levels into Interpretable Text |
rarefySamples | Data Rarefaction |
readdepth | Get read depth summary statistics for each group or for all... |
removeGrps | Remove Groups |
removeLowQuality | Remove Low Quality Samples |
removePool | Remove a factor of pooled groups |
removeSamples | Remove Specific Samples |
resetResDir | Reset the Results Directory |
rfboruta | Perform random forest Boruta analysis |
runFeatureFilter | Feature Filter |
runFeatureRemover | Feature Remover |
runNormalization | Data Normalization |
runRarefaction | Rarefy Dataset |
runSampleFilter | Sample Filter |
sampleFreq | Frequency table of samples |
samplesWith | Filter a datatable to only samples with certain metadata... |
saveResults | Save figure and statistics results |
savetoggle | Switch Saving Mode |
scaleFeatures | Scale Features |
scaleSamples | Scale Samples |
selectFeatures | Select Specific Features |
setFVar | Set Factor Variable |
sliceCormats | Select only significant and/or high-correlation values from... |
sparcc | Sparcc wrapper |
sparccboot | Bootstrap SparCC |
summarizeTaxa | Get mean and SE of features |
TaxatoASV | Translate Taxa Names to ASV Numbers |
theme_mv | MicroVis ggplot theme |
transData | Data Transformation |
univar | Perform Univariate Analysis |
unselectFeatures | Undo Feature Selection |
validFactor | Factor Validation |
viewactive | View the active dataset in RStudio Viewer |
viewstats | View Statistics of All Features |
viewtable | View Abundance Table |
zeroReplace | Replace Zeros with Non-Zero Value |
zerostoggle | Switch Method for Replacing Zeros |
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