Microbiome analysis

Documentation for package ‘mia’ version 1.6.0

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'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