Function reference • mia

Data handling
Agglomeration
`agglomerateByRank()` `mergeFeaturesByRank()` `agglomerateByPrevalence()`	Agglomerate data using taxonomic information
`mergeRows()` `mergeCols()` `mergeFeatures()` `mergeSamples()`	Merge a subset of the rows or columns of a `SummarizedExperiment`
`splitByRanks()` `unsplitByRanks()`	Split/Unsplit a `SingleCellExperiment` by taxonomic ranks
`splitOn()` `unsplitOn()`	Split `TreeSummarizedExperiment` column-wise or row-wise based on grouping variable
`mergeSEs()`	Merge SE objects into single SE object.
Transformation
`transformSamples()` `transformAssay()` `transformCounts()` `transformFeatures()` `ZTransform()` `relAbundanceCounts()`	Transform assay
Data loading
`makeTreeSEFromPhyloseq()` `makeTreeSummarizedExperimentFromPhyloseq()`	Coerce a `phyloseq` object to a `TreeSummarizedExperiment`
`makeTreeSEFromDADA2()` `makeTreeSummarizedExperimentFromDADA2()`	Coerce ‘DADA2’ results to `TreeSummarizedExperiment`
`importBIOM()` `makeTreeSEFromBiom()` `makeTreeSummarizedExperimentFromBiom()`	Loading a biom file
`importQIIME2()` `importQZA()`	Import QIIME2 results to `TreeSummarizedExperiment`
`importMothur()`	Import Mothur results as a `TreeSummarizedExperiment`
`importMetaPhlAn`	Import Metaphlan results to `TreeSummarizedExperiment`
`importHUMAnN`	Import HUMAnN results to `TreeSummarizedExperiment`
`makePhyloseqFromTreeSE()` `makePhyloseqFromTreeSummarizedExperiment()`	Create a phyloseq object from a TreeSummarizedExperiment object
Taxonomic data
`TAXONOMY_RANKS` `taxonomyRanks()` `taxonomyRankEmpty()` `checkTaxonomy()` `setTaxonomyRanks()` `getTaxonomyRanks()` `getTaxonomyLabels()` `mapTaxonomy()` `IdTaxaToDataFrame()`	Functions for accessing taxonomic data stored in `rowData`.
Diversity indeces
Alpha Diversity
`estimateDiversity()` `estimateFaith()`	Estimate (alpha) diversity measures
`addDivergence()`	Estimate divergence
Beta Diversity
`calculateUnifrac()` `runUnifrac()`	Calculate weighted or unweighted (Fast) Unifrac distance
`calculateJSD(<ANY>)` `calculateJSD(<SummarizedExperiment>)` `runJSD()`	Calculate the Jensen-Shannon Divergence
`calculateNMDS()` `runNMDS()`	Perform non-metric MDS on sample-level data
`calculateCCA()` `runCCA()` `calculateRDA()` `runRDA()`	Canonical Correspondence Analysis and Redundancy Analysis
`calculateOverlap()` `runOverlap()`	Estimate overlap
Other diversity measurements
`calculateDPCoA()` `runDPCoA()`	Calculation of Double Principal Correspondance analysis
`estimateRichness()`	Estimate richness measures
Other functions
Dataset description
`getPrevalence()` `getPrevalentFeatures()` `getPrevalentTaxa()` `getRareFeatures()` `getRareTaxa()` `subsetByPrevalentFeatures()` `subsetByPrevalentTaxa()` `subsetByRareFeatures()` `subsetByRareTaxa()` `getPrevalentAbundance()`	Calculation prevalence information for features across samples
`getTopFeatures()` `getTopTaxa()` `getUniqueFeatures()` `getUniqueTaxa()` `countDominantFeatures()` `countDominantTaxa()` `summary(<SummarizedExperiment>)`	Summarizing microbiome data
`getExperimentCrossAssociation()` `testExperimentCrossAssociation()` `testExperimentCrossCorrelation()` `getExperimentCrossCorrelation()`	Calculate correlations between features of two experiments.
`getHierarchyTree()` `addHierarchyTree()`	Calculate hierarchy tree
Dominance
`perSampleDominantFeatures()` `perSampleDominantTaxa()` `addPerSampleDominantFeatures()` `addPerSampleDominantTaxa()`	Get dominant taxa
`estimateDominance()`	Estimate dominance measures
Evenness indeces
`estimateEvenness()`	Estimate Evenness measures
Clustering
`calculateDMN()` `runDMN()` `getDMN()` `bestDMNFit()` `getBestDMNFit()` `calculateDMNgroup()` `performDMNgroupCV()`	Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
`addCluster()`	Clustering wrapper
decontam
`isContaminant(<SummarizedExperiment>)` `isNotContaminant(<SummarizedExperiment>)` `addContaminantQC()` `addNotContaminantQC()`	decontam functions
Helper
`meltAssay()`	Converting a `SummarizedExperiment` object into a long data.frame
`relabundance()` `relabundance<-`()	Getter / setter for relative abundance data
`subsampleCounts()`	Subsample Counts
`subsetSamples()` `subsetFeatures()` `subsetTaxa()`	Subset functions
Datasets
`mia-datasets`	mia datasets
`dmn_se`	dmn_se
`enterotype`	enterotype
`esophagus`	esophagus
`GlobalPatterns`	GlobalPatterns
`HintikkaXOData`	HintikkaXOData
`peerj13075`	peerj13075
`Tengeler2020`	Tengeler2020
Package
`mia` `mia-package`	`mia` Package.
Deprecated functions
`cluster()` `addTaxonomyTree()` `taxonomyTree()` `mergeFeaturesByPrevalence()` `loadFromBiom()` `loadFromQIIME2()` `readQZA()` `loadFromMothur()` `loadFromMetaphlan()` `loadFromHumann()` `full_join()` `inner_join()` `left_join()` `right_join()` `plotNMDS()` `estimateDivergence()`	These functions will be deprecated. Please use other functions instead.

Reference

Data handling

Agglomeration

Transformation

Data loading

Taxonomic data

Diversity indeces

Alpha Diversity

Beta Diversity

Other diversity measurements

Other functions

Dataset description

Dominance

Evenness indeces

Clustering

decontam

Helper

Datasets

Package

Deprecated functions