Package: microbiomeExplorer 1.15.0

Janina Reeder

microbiomeExplorer: Microbiome Exploration App

The MicrobiomeExplorer R package is designed to facilitate the analysis and visualization of marker-gene survey feature data. It allows a user to perform and visualize typical microbiome analytical workflows either through the command line or an interactive Shiny application included with the package. In addition to applying common analytical workflows the application enables automated analysis report generation.

Authors:Joseph Paulson [aut], Janina Reeder [aut, cre], Mo Huang [aut], Genentech [cph, fnd]

microbiomeExplorer_1.15.0.tar.gz
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microbiomeExplorer_1.15.0.tgz(r-4.4-any)microbiomeExplorer_1.15.0.tgz(r-4.3-any)
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microbiomeExplorer.pdf |microbiomeExplorer.html
microbiomeExplorer/json (API)
NEWS

# Install 'microbiomeExplorer' in R:
install.packages('microbiomeExplorer', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On BioConductor:microbiomeExplorer-1.15.0(bioc 3.20)microbiomeExplorer-1.14.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

37 exports 0.49 score 181 dependencies

Last updated 2 months agofrom:30362016e9

Exports:addFeatDataaddPhenoDataaggFeaturesaggregationTabUIcalculatePCAscomputeDistMatcorrAnalysisUIcorrFeaturecorrPhenotypedataInputUIdiffAnalysisUIextendPhenoDatafeatureAnalysisUIfeatureTableUIfilterByPhenofilterMEDatainterAnalysisUIintraAnalysisUIlongAnalysisUImakeQCPlotnormalizeDataphenotypeTableUIplotAbundanceplotAlphaplotAvgAbundanceplotBetaplotHeatmapplotLongFeatureplotlyHistogramplotlySampleBarplotplotSingleFeaturereadDatareplaceWithUnknownreportListUIrollDownFeaturesrunDiffTestrunMicrobiomeExplorer

Dependencies:abindanytimeaskpassassertthatbackportsbase64encBHBiobaseBiocGenericsBiocParallelbiomformatbitbit64bitopsbootbroombslibcacachemcallrcarcarDatacaToolsclicliprclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDelayedArraydendextendDerivDESeq2digestdoBydplyrDTeggevaluatefansifarverfastmapfontawesomeforcatsforeachformatRfsfutile.loggerfutile.optionsgclusgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2glmnetgluegplotsgridExtragtablegtoolsheatmaplyhighrhmshtmltoolshtmlwidgetshttpuvhttrIRangesisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalme4locfitlubridatemagrittrMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemetagenomeSeqmgcvmicrobenchmarkmimeminqamodelrmunsellnlmenloptrnnetnumDerivopensslpbkrtestpermutepillarpkgconfigplotlyplyrprettyunitsprocessxprogresspromisespspurrrqapquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenreadrregistryreshape2rhdf5rhdf5filtersRhdf5librlangrmarkdownS4ArraysS4VectorssassscalesseriationshapeshinyshinycssloadersshinydashboardshinyjsshinyWidgetssnowsourcetoolsSparseArraySparseMstatmodstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttimechangetinytexTSPtzdbUCSC.utilsutf8vctrsveganviridisviridisLitevroomwebshotwithrWrenchxfunxtableXVectoryamlzlibbioc

Using Microbiome Explorer application to analyze amplicon sequencing data

Rendered fromexploreMouseData.Rmdusingknitr::rmarkdownon Jul 02 2024.

Last update: 2020-10-06
Started: 2020-07-27

Readme and manuals

Help Manual

Help pageTopics
Abundance Heatmap module - serverabundanceHeatmap
Abundance Heatmap module - UIabundanceHeatmapUI
Adds a config call based on plotly::configadd_plotly_config
Adds a layout call based on plotly::layoutadd_plotly_layout
Add feature data to MRobj.addFeatData
Add phenotype data to object.addPhenoData
Aggregates counts by levelaggFeatures
Aggregation module server functionaggregationTab
Aggregation module ui functionaggregationTabUI
Alpha Diversity module - serveralphaDiversity
Alpha Diversity module - UIalphaDiversityUI
Relative abundance plot module - serveravgAbundance
Relative abundance plot module - UIavgAbundanceUI
Beta Diversity module - serverbetaDiversity
Beta Diversity module - UIbetaDiversityUI
Server side for the analysis input module handling analysis controlbetaInput
Main beta analysis input module. Set up to handle all analysis tabs in the app depending on given parametersbetaInputUI
Creates an empty plotly plot using the given labels on the x and y axisbuildEmptyPlotlyPlot
Sets up a dataframe used by several plotting functions by joining the required data with relevant phenotype databuildPlottingDF
Function to compute the PCAs for a given distance matrixcalculatePCAs
Helper function to calculate the confidence interval for a cor.testcomputeCI_Interval
Function to compute the distance matrix using vegdist from the vegan packagecomputeDistMat
corr Analysis Module - servercorrAnalysis
corr Analysis Module - UIcorrAnalysisUI
Scatterplot of two featurescorrFeature
Server side for the analysis input module handling analysis controlcorrInput
Main correlation analysis input module. Handles correlation analysis tab in the appcorrInputUI
Scatterplot of a feature and a phenotypecorrPhenotype
Makes header for R scriptcreateHeader
Main Data input server where the user selects files to upload to the app or connects to databasedataInput
Main Data input UI where the user selects files to upload to the app or connects to databasedataInputUI
Produce design matrix of pairwise comparisonsdesignPairs
diff Analysis Module - serverdiffAnalysis
Diff Analysis Module - UIdiffAnalysisUI
Server side for the analysis input module handling analysis controldiffInput
Main diffanalysis input module. Set up to handle diff analysis tabs in the app depending on given parametersdiffInputUI
Differential analysis module server codediffTable
Differential Analysis module UIdiffTableUI
Extends existing phenodata for an objectextendPhenoData
Feature plot module - serverfeatAbundance
Feature plot module - UIfeatAbundanceUI
feature Analysis Module - serverfeatureAnalysis
feature Analysis Module - UIfeatureAnalysisUI
Feature correlation analysis server modulefeatureCorr
Feature correlation analysis module UIfeatureCorrUI
Server side for the feature analysis input modulefeatureInput
Main feature analysis input module. Set up to handle all analysis tabs in the app depending on given parametersfeatureInputUI
Feature table module server codefeatureTable
Feature table UI modulefeatureTableUI
Module handling file upload for the application: serverfileUpload
Module handling file upload for the application: UI In a deployed version this module should be replaced with database accessfileUploadUI
Function to filter the MRexperiment by certain phenotype valuesfilterByPheno
Function to filter the MRexperiment data by numerical parametersfilterMEData
Generates reportgenerateReport
Helper function returning the fData modifications as strings for report generationgetFeatModCode
Helper function returning the fData modifications as strings for report generationgetFeatSplitCode
Helper function assigning different file extensions to specific short texts identifying the typesgetFileType
Helper function to filter phenodata for interesting phenotypes to be used for filtering or subsettinggetFilterChoices
Function to find a non-empty facet in the last row. This will be the one to be connected to the plot legend to avoid duplicates withingetLegendLevel
Helper function returning the code used to modify the data types of the pheno tablegetPhenoChanges
Helper function returning the code used to modify the phenotable as a stringgetPhenoModCode
Helper function to account for issues plotly has with very small widths (these end up being 1 and cover the entire plotting area)getWidths
Server side for the analysis input module handling analysis controlheatmapInput
Heatmap analysis input module. Set up to handle all analysis tabs in the app depending on given parametersheatmapInputUI
inter Analysis Module - serverinterAnalysis
inter Analysis Module - UIinterAnalysisUI
Intra Analysis Module - serverintraAnalysis
Intra Analysis Module - UIintraAnalysisUI
Server side for the intra analysis input moduleintraInput
Main intra analysis input module. Set up to handle all analysis tabs in the app depending on given parametersintraInputUI
long Analysis Module - serverlongAnalysis
Long Analysis Module - UIlongAnalysisUI
Server side for the analysis input module handling analysis controllongInput
Main diffanalysis input module. Set up to handle diff analysis tabs in the app depending on given parameterslongInputUI
Longitudinal analysis module server codelongResults
Longitudinal Analysis module UIlongResultsUI
Plots sequencing statistics scatterplotmakeQCPlot
Calls appropriate normalization functions depending on input parameter The two available methods included in the package are based on either calculating proportions or by using cumulative sum scaling (CSS), Paulson, et al. Nat Meth 2013.normalizeData
Helper function used to build a correct interactionName based on the chosen columnsparseInteractionName
Phenotype correlation analysis server modulephenotypeCorr
Phenotype correlation analysis modulephenotypeCorrUI
Phenotype table server modulephenotypeTable
Phenotype table UI modulephenotypeTableUI
Plot relative abundanceplotAbundance
Plot alpha diversityplotAlpha
Plot average relative abundanceplotAvgAbundance
Plot beta diversityplotBeta
Plot heatmapplotHeatmap
Plot longitudinal featuresplotLongFeature
Function plotting a plotly histogram on the given histvalueplotlyHistogram
Function plotting a barplot showing number of OTUs per samplesplotlySampleBarplot
Plot featuresplotSingleFeature
Reads in datareadData
Relative abundance plot module - serverrelAbundance
Relative abundance plot module - UIrelAbundanceUI
Helper function to replace any un-annotated features with the term unknownreplaceWithUnknown
Report tab module serverreportList
report tab uireportListUI
Report RowreportRow
Report row module consisting of a checkbox, image and description/R code areareportRowUI
Helper function which rolls down annotated from closest higher order with annotationrollDownFeatures
Performs differential abundance testingrunDiffTest
Main function to start the Microbiome Explorer Shiny app via a command line callrunMicrobiomeExplorer