# Microbiome analysis

## Documentation for package ‘mia’ version 1.8.0

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

## Help Pages

A B C D E F G H 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
addPerSampleDominantFeatures | Get dominant taxa
addPerSampleDominantFeatures-method | Get dominant taxa
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 Correspondence Analysis
calculateCCA-method | Canonical Correspondence Analysis
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
calculateOverlap | Estimate overlap
calculateOverlap-method | Estimate overlap
calculateRDA | Canonical Correspondence Analysis
calculateRDA-method | Canonical Correspondence 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'.
countDominantFeatures | Summarizing microbiome data
countDominantFeatures-method | Summarizing microbiome data
countDominantTaxa | Summarizing microbiome data
countDominantTaxa-method | Summarizing microbiome data

## -- D --

dmn_se | mia datasets
dmn_se, | mia datasets

## -- E --

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

## -- F --

full_join | Merge SE objects into single SE object.
full_join-method | Merge SE objects into single SE object.

## -- 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
getExperimentCrossAssociation | Calculate correlations between features of two experiments.
getExperimentCrossAssociation-method | Calculate correlations between features of two experiments.
getExperimentCrossCorrelation | Calculate correlations between features of two experiments.
getExperimentCrossCorrelation-method | Calculate correlations between features of two experiments.
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
getPrevalentFeatures | Calculation prevalence information for features across samples
getPrevalentFeatures-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
getRareFeatures | Calculation prevalence information for features across samples
getRareFeatures-method | Calculation prevalence information for features across samples
getRarePrevalentFeatures | 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'.
getTopFeatures | Summarizing microbiome data
getTopFeatures-method | Summarizing microbiome data
getTopTaxa | Summarizing microbiome data
getTopTaxa-method | Summarizing microbiome data
getUniqueFeatures | Summarizing microbiome data
getUniqueFeatures-method | Summarizing microbiome data
getUniqueTaxa | Summarizing microbiome data
getUniqueTaxa-method | Summarizing microbiome data
GlobalPatterns | mia datasets

## -- H --

HintikkaXOData | mia datasets

## -- I --

IdTaxaToDataFrame | Functions for accessing taxonomic data stored in 'rowData'.
inner_join | Merge SE objects into single SE object.
inner_join-method | Merge SE objects into single SE object.
isContaminant | decontam functions
isContaminant-method | decontam functions
isNotContaminant-method | decontam functions

## -- L --

left_join | Merge SE objects into single SE object.
left_join-method | Merge SE objects into single SE object.
loadFromBiom | Loading a biom file
loadFromMetaphlan | Import Metaphlan results to 'TreeSummarizedExperiment'
loadFromMothur | Import Mothur results as a 'TreeSummarizedExperiment'
loadFromQIIME2 | Import QIIME2 results to 'TreeSummarizedExperiment'

## -- M --

makePhyloseqFromTreeSE | Create a phyloseq object from a TreeSummarizedExperiment object
makePhyloseqFromTreeSE-method | Create a phyloseq object from a TreeSummarizedExperiment object
makePhyloseqFromTreeSummarizedExperiment | Create a phyloseq object from a TreeSummarizedExperiment object
makePhyloseqFromTreeSummarizedExperiment-method | Create a phyloseq object from a TreeSummarizedExperiment object
makeTreeSEFromBiom | Loading a biom file
makeTreeSEFromDADA2 | Coerce 'DADA2' results to 'TreeSummarizedExperiment'
makeTreeSEFromPhyloseq | Coerce a 'phyloseq' object to a 'TreeSummarizedExperiment'
makeTreeSummarizedExperimentFromBiom | Loading a biom file
makeTreeSummarizedExperimentFromDADA2 | Coerce 'DADA2' results to 'TreeSummarizedExperiment'
makeTreeSummarizedExperimentFromPhyloseq | Coerce a 'phyloseq' object to a 'TreeSummarizedExperiment'
makeTreeSummarizedExperimentFromPhyloseq-method | 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'
mergeSEs | Merge SE objects into single SE object.
mergeSEs-method | Merge SE objects into single SE object.
mia-datasets | mia datasets

## -- P --

peerj13075 | mia datasets
performDMNgroupCV | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
performDMNgroupCV-method | Dirichlet-Multinomial Mixture Model: Machine Learning for Microbiome Data
perSampleDominantFeatures | Get dominant taxa
perSampleDominantFeatures-method | Get dominant taxa
perSampleDominantTaxa | Get dominant taxa
perSampleDominantTaxa-method | Get dominant taxa
plotNMDS | Perform non-metric MDS on sample-level data

## -- R --

rarifyCounts | Subsample Counts
readQZA | Import QIIME2 results to 'TreeSummarizedExperiment'
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
right_join | Merge SE objects into single SE object.
right_join-method | Merge SE objects into single SE object.
runCCA | Canonical Correspondence Analysis
runCCA-method | Canonical Correspondence 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
runOverlap | Estimate overlap
runOverlap-method | Estimate overlap
runRDA | Canonical Correspondence Analysis
runRDA-method | Canonical Correspondence Analysis
runUnifrac | Calculate weighted or unweighted (Fast) Unifrac distance

## -- S --

splitByRanks | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks
splitByRanks-method | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks
splitOn | Split 'TreeSummarizedExperiment' column-wise or row-wise based on grouping variable
splitOn-method | Split 'TreeSummarizedExperiment' column-wise or row-wise based on grouping variable
subsampleCounts | Subsample Counts
subsampleCounts-method | Subsample Counts
subsetByPrevalentFeatures | Calculation prevalence information for features across samples
subsetByPrevalentFeatures-method | Calculation prevalence information for features across samples
subsetByPrevalentTaxa | Calculation prevalence information for features across samples
subsetByPrevalentTaxa-method | Calculation prevalence information for features across samples
subsetByRareFeatures | Calculation prevalence information for features across samples
subsetByRareFeatures-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 --

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'.
testExperimentCrossAssociation | Calculate correlations between features of two experiments.
testExperimentCrossAssociation-method | Calculate correlations between features of two experiments.
testExperimentCrossCorrelation | Calculate correlations between features of two experiments.
testExperimentCrossCorrelation-method | Calculate correlations between features of two experiments.
transformCounts | Transform Counts
transformCounts-method | Transform Counts
transformFeatures | Transform Counts
transformFeatures-method | Transform Counts
transformSamples | Transform Counts
transformSamples-method | Transform Counts
twins | mia datasets

## -- U --

unsplitByRanks | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks
unsplitByRanks-method | Split/Unsplit a 'SingleCellExperiment' by taxonomic ranks
unsplitOn | Split 'TreeSummarizedExperiment' column-wise or row-wise based on grouping variable
unsplitOn-method | Split 'TreeSummarizedExperiment' column-wise or row-wise based on grouping variable

## -- Z --

ZTransform | Transform Counts
ZTransform-method | Transform Counts