# Microbiome analysis

## Documentation for package ‘mia’ version 1.2.7

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E G I L M P R S T U Z

mia-package | 'mia' Package.

## -- A --

addContaminantQC | decontam functions
addContaminantQC-method | decontam functions
addNotContaminantQC | decontam functions
addNotContaminantQC-method | decontam functions
addPerSampleDominantTaxa | Get dominant taxa
addPerSampleDominantTaxa-method | Get dominant taxa
addTaxonomyTree | Functions for accessing taxonomic data stored in 'rowData'.
addTaxonomyTree-method | Functions for accessing taxonomic data stored in 'rowData'.
agglomerate-methods | Agglomerate data using taxonomic information
agglomerateByPrevalence | Calculation prevalence information for features across samples
agglomerateByPrevalence-method | Calculation prevalence information for features across samples
agglomerateByRank | Agglomerate data using taxonomic information
agglomerateByRank-method | Agglomerate data using taxonomic information

## -- B --

bestDMNFit | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
bestDMNFit-method | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data

## -- C --

calculateCCA | Canonical Correspondance Analysis
calculateCCA-method | Canonical Correspondance Analysis
calculateDistance | Calculate sample distances with 'vegan'
calculateDistance-method | Calculate sample distances with 'vegan'
calculateDMN | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
calculateDMN-method | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
calculateDMNgroup | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
calculateDMNgroup-method | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
calculateDPCoA | Calculation of Double Principal Correspondance analysis
calculateDPCoA-method | Calculation of Double Principal Correspondance analysis
calculateJSD | Calculate the Jensen-Shannon Divergence
calculateJSD-method | Calculate the Jensen-Shannon Divergence
calculateNMDS | Perform non-metric MDS on sample-level data
calculateNMDS-method | Perform non-metric MDS on sample-level data
calculateRDA | Canonical Correspondance Analysis
calculateRDA-method | Canonical Correspondance Analysis
calculateUniFrac | Calculate weighted or unweighted (Fast) UniFrac distance
calculateUniFrac-method | Calculate weighted or unweighted (Fast) UniFrac distance
checkTaxonomy | Functions for accessing taxonomic data stored in 'rowData'.
checkTaxonomy-method | Functions for accessing taxonomic data stored in 'rowData'.
countDominantTaxa | Summarizing microbiome data
countDominantTaxa-method | Summarizing microbiome data

## -- D --

dmn_se | mia datasets

## -- E --

enterotype | mia datasets
esophagus | mia datasets
estimateDivergence | Estimate divergence
estimateDivergence-method | Estimate divergence
estimateDiversity | Estimate diversity measures
estimateDiversity-method | Estimate diversity measures
estimateDominance | Estimate dominance measures
estimateDominance-method | Estimate dominance measures
estimateEvenness | Estimate Evenness measures
estimateEvenness-method | Estimate Evenness measures
estimateFaith | Estimate diversity measures
estimateFaith-method | Estimate diversity measures
estimateRichness | Estimate richness measures
estimateRichness-method | Estimate richness measures

## -- G --

getAbundance | Get abundance values by "SampleID" or "FeatureID"
getAbundanceFeature | Get abundance values by "SampleID" or "FeatureID"
getAbundanceFeature-method | Get abundance values by "SampleID" or "FeatureID"
getAbundanceSample | Get abundance values by "SampleID" or "FeatureID"
getAbundanceSample-method | Get abundance values by "SampleID" or "FeatureID"
getBestDMNFit | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
getBestDMNFit-method | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
getDMN | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
getDMN-method | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
getExperimentCrossCorrelation | Calculate cross-correlation
getExperimentCrossCorrelation-method | Calculate cross-correlation
getPrevalence | Calculation prevalence information for features across samples
getPrevalence-method | Calculation prevalence information for features across samples
getPrevalentAbundance | Calculation prevalence information for features across samples
getPrevalentAbundance-method | Calculation prevalence information for features across samples
getPrevalentTaxa | Calculation prevalence information for features across samples
getPrevalentTaxa-method | Calculation prevalence information for features across samples
getRareTaxa | Calculation prevalence information for features across samples
getRareTaxa-method | Calculation prevalence information for features across samples
getTaxonomyLabels | Functions for accessing taxonomic data stored in 'rowData'.
getTaxonomyLabels-method | Functions for accessing taxonomic data stored in 'rowData'.
getTopTaxa | Summarizing microbiome data
getTopTaxa-method | Summarizing microbiome data
getUniqueTaxa | Summarizing microbiome data
getUniqueTaxa-method | Summarizing microbiome data
GlobalPatterns | mia datasets

## -- I --

IdTaxaToDataFrame | Functions for accessing taxonomic data stored in 'rowData'.
isContaminant | decontam functions
isContaminant-method | decontam functions
isNotContaminant-method | decontam functions

## -- L --

loadFromBiom | Loading a biom file
loadFromMothur | Import Mothur results as a 'SummarizedExperiment'
loadFromQIIME2 | Import QIIME2 results to 'TreeSummarizedExperiment'

## -- M --

makePhyloseqFromTreeSummarizedExperiment | Create a phyloseq object from a TreeSummarizedExperiment object
makePhyloseqFromTreeSummarizedExperiment-method | Create a phyloseq object from a TreeSummarizedExperiment object
makeSummarizedExperimentFromBiom | Loading a biom file
makeTreeSummarizedExperimentFromDADA2 | Coerce 'DADA2' results to 'TreeSummarizedExperiment'
makeTreeSummarizedExperimentFromPhyloseq | Coerce a 'phyloseq' object to a 'TreeSummarizedExperiment'
mapTaxonomy | Functions for accessing taxonomic data stored in 'rowData'.
mapTaxonomy-method | Functions for accessing taxonomic data stored in 'rowData'.
meltAssay | Converting a 'SummarizedExperiment' object into a long data.frame
meltAssay-method | Converting a 'SummarizedExperiment' object into a long data.frame
merge-methods | Merge a subset of the rows or columns of a 'SummarizedExperiment'
mergeCols | Merge a subset of the rows or columns of a 'SummarizedExperiment'
mergeCols-method | Merge a subset of the rows or columns of a 'SummarizedExperiment'
mergeRows | Merge a subset of the rows or columns of a 'SummarizedExperiment'
mergeRows-method | Merge a subset of the rows or columns of a 'SummarizedExperiment'
mia-datasets | mia datasets

## -- P --

performDMNgroupCV | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
performDMNgroupCV-method | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
perSampleDominantTaxa | Get dominant taxa
perSampleDominantTaxa-method | Get dominant taxa
plotNMDS | Perform non-metric MDS on sample-level data

## -- R --

relabundance | Getter / setter for relative abundance data
relabundance-method | Getter / setter for relative abundance data
relabundance<- | Getter / setter for relative abundance data
relabundance<--method | Getter / setter for relative abundance data
relAbundanceCounts | Transform Counts
relAbundanceCounts-method | Transform Counts
runCCA | Canonical Correspondance Analysis
runCCA-method | Canonical Correspondance Analysis
runDMN | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
runDPCoA | Calculation of Double Principal Correspondance analysis
runJSD | Calculate the Jensen-Shannon Divergence
runNMDS | Perform non-metric MDS on sample-level data
runRDA | Canonical Correspondance Analysis
runRDA-method | Canonical Correspondance Analysis
runUniFrac | Calculate weighted or unweighted (Fast) UniFrac distance

## -- S --

soilrep | mia datasets
splitByRanks | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks
splitByRanks-method | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks
subsetByPrevalentTaxa | Calculation prevalence information for features across samples
subsetByPrevalentTaxa-method | Calculation prevalence information for features across samples
subsetByRareTaxa | Calculation prevalence information for features across samples
subsetByRareTaxa-method | Calculation prevalence information for features across samples
subsetFeatures | Subset functions
subsetFeatures-method | Subset functions
subsetSamples | Subset functions
subsetSamples-method | Subset functions
subsetTaxa | Subset functions
subsetTaxa-method | Subset functions
summaries | Summarizing microbiome data
summary-method | Summarizing microbiome data

## -- T --

taxonomicRanks | Functions for accessing taxonomic data stored in 'rowData'.
taxonomy-methods | Functions for accessing taxonomic data stored in 'rowData'.
taxonomyRankEmpty | Functions for accessing taxonomic data stored in 'rowData'.
taxonomyRankEmpty-method | Functions for accessing taxonomic data stored in 'rowData'.
taxonomyRanks | Functions for accessing taxonomic data stored in 'rowData'.
taxonomyRanks-method | Functions for accessing taxonomic data stored in 'rowData'.
taxonomyTree | Functions for accessing taxonomic data stored in 'rowData'.
taxonomyTree-method | Functions for accessing taxonomic data stored in 'rowData'.
TAXONOMY_RANKS | Functions for accessing taxonomic data stored in 'rowData'.
testForExperimentCrossCorrelation | Calculate cross-correlation
testForExperimentCrossCorrelation-method | Calculate cross-correlation
transformCounts | Transform Counts
transformCounts-method | Transform Counts
transformFeatures | Transform Counts
transformFeatures-method | Transform Counts
transformSamples | Transform Counts
transformSamples-method | Transform Counts

## -- U --

unsplitByRanks | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks
unsplitByRanks-method | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks

## -- Z --

ZTransform | Transform Counts
ZTransform-method | Transform Counts