veupathUtils -> mbioUtils

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: MicrobiomeDB
 Title: Curated Data and Analysis Tools from MicrobiomeDB.org
-Version: 1.1.1
+Version: 1.1.2
 Authors@R:
     c(person(given = "Danielle",
             family = "Callan",
@@ -12,15 +12,15 @@ Imports:
     data.table,
     DESeq2,
     igraph,
-    veupathUtils,
+    mbioUtils (>= 0.1.0),
     Maaslin2,
     methods,
-    microbiomeComputations,
+    microbiomeComputations (>= 5.1.7),
     purrr,
     SummarizedExperiment,
     TreeSummarizedExperiment
 Remotes:
-    microbiomeDB/veupathUtils,
+    microbiomeDB/mbioUtils,
     microbiomeDB/corGraph,
     microbiomeDB/microbiomeComputations,
     microbiomeDB/microbiomeData
@@ -30,7 +30,7 @@ Description: This package is intended to be used to explore the curated datasets
 License: Apache License (>= 2)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.3
 Suggests: 
     testthat (>= 3.0.0),
     S4Vectors,

NAMESPACE

@@ -38,6 +38,25 @@ importFrom(corGraph,bipartiteNetwork)
 importFrom(corGraph,unipartiteNetwork)
 importFrom(data.table,data.table)
 importFrom(igraph,graph_from_data_frame)
+importFrom(mbioUtils,Collection)
+importFrom(mbioUtils,Collections)
+importFrom(mbioUtils,ComputeResult)
+importFrom(mbioUtils,CorrelationResult)
+importFrom(mbioUtils,SampleMetadata)
+importFrom(mbioUtils,VariableSpec)
+importFrom(mbioUtils,correlation)
+importFrom(mbioUtils,findAncestorIdColumns)
+importFrom(mbioUtils,findRecordIdColumn)
+importFrom(mbioUtils,getCollectionNames)
+importFrom(mbioUtils,getCollectionVariableNames)
+importFrom(mbioUtils,getDataFromSource)
+importFrom(mbioUtils,getIdColumns)
+importFrom(mbioUtils,getMetadataVariableNames)
+importFrom(mbioUtils,getMetadataVariableSummary)
+importFrom(mbioUtils,getSampleMetadata)
+importFrom(mbioUtils,getSampleMetadataIdColumns)
+importFrom(mbioUtils,matchArg)
+importFrom(mbioUtils,selfCorrelation)
 importFrom(microbiomeComputations,AbsoluteAbundanceData)
 importFrom(microbiomeComputations,AbundanceData)
 importFrom(microbiomeComputations,Comparator)
@@ -48,22 +67,3 @@ importFrom(microbiomeComputations,internalDiffAbund)
 importFrom(microbiomeComputations,rankedAbundance)
 importFrom(microbiomeComputations,selfCorrelation)
 importFrom(purrr,reduce)
-importFrom(veupathUtils,Collection)
-importFrom(veupathUtils,Collections)
-importFrom(veupathUtils,ComputeResult)
-importFrom(veupathUtils,CorrelationResult)
-importFrom(veupathUtils,SampleMetadata)
-importFrom(veupathUtils,VariableSpec)
-importFrom(veupathUtils,correlation)
-importFrom(veupathUtils,findAncestorIdColumns)
-importFrom(veupathUtils,findRecordIdColumn)
-importFrom(veupathUtils,getCollectionNames)
-importFrom(veupathUtils,getCollectionVariableNames)
-importFrom(veupathUtils,getDataFromSource)
-importFrom(veupathUtils,getIdColumns)
-importFrom(veupathUtils,getMetadataVariableNames)
-importFrom(veupathUtils,getMetadataVariableSummary)
-importFrom(veupathUtils,getSampleMetadata)
-importFrom(veupathUtils,getSampleMetadataIdColumns)
-importFrom(veupathUtils,matchArg)
-importFrom(veupathUtils,selfCorrelation)

R/class-MbioDataset.R

@@ -22,7 +22,7 @@ check_mbio_dataset <- function(object) {
 #' This class represents a MicrobiomeDB dataset.
 #' @name MbioDataset-class
 #' @rdname MbioDataset-class
-#' @importFrom veupathUtils SampleMetadata
+#' @importFrom mbioUtils SampleMetadata
 setClass("MbioDataset", 
     slots = c(
         collections = "Collections",

R/importers-MbioDataset.R

@@ -6,7 +6,7 @@ buildCollectionFromTreeSE <- function(
     normalizationMethod = c("TSS", "none"),
     verbose = c(TRUE, FALSE)
 ) {
-    verbose <- veupathUtils::matchArg(verbose)
+    verbose <- mbioUtils::matchArg(verbose)
 
     assayDataName <- collectionName$assayDataName
     rowDataColumnName <- collectionName$rowDataColumnName
@@ -66,7 +66,7 @@ buildCollectionFromTreeSE <- function(
         collectionName <- paste0(collectionName, " (", normalizationMethod, " normalized)")
     }
 
-    collection <- veupathUtils::Collection(
+    collection <- mbioUtils::Collection(
         data = dt,
         recordIdColumn = recordIdColumn,
         ancestorIdColumns = ancestorIdColumns,
@@ -125,9 +125,9 @@ buildCollectionFromTreeSE <- function(
 #' @export
 importTreeSummarizedExperiment <- function(data, normalizationMethod = c("TSS", "none"), keepRawValues = c(TRUE, FALSE), verbose = c(TRUE, FALSE)) {
 
-    normalizationMethod <- veupathUtils::matchArg(normalizationMethod)
-    keepRawValues <- veupathUtils::matchArg(keepRawValues)
-    verbose <- veupathUtils::matchArg(verbose)
+    normalizationMethod <- mbioUtils::matchArg(normalizationMethod)
+    keepRawValues <- mbioUtils::matchArg(keepRawValues)
+    verbose <- mbioUtils::matchArg(verbose)
 
     if (!inherits(data, "SummarizedExperiment")) {
         stop("data must be or extend a SummarizedExperiment")
@@ -182,7 +182,7 @@ importTreeSummarizedExperiment <- function(data, normalizationMethod = c("TSS",
 
         collectionsList <- c(rawCollectionsList, normalizedCollectionsList)
     } else {
-        collectionsList <- veupathUtils::Collections()
+        collectionsList <- mbioUtils::Collections()
     }
 
 

R/method-differentialAbundance.R

@@ -31,23 +31,23 @@ assignToBinaryGroups <- function(x, groupAPredicate, groupBPredicate = NULL) {
     return(x)
 }
 
-#' @importFrom veupathUtils VariableSpec
-#' @importFrom veupathUtils getIdColumns
+#' @importFrom mbioUtils VariableSpec
+#' @importFrom mbioUtils getIdColumns
 buildBinaryComparator <- function(covariate, groupAValue, groupBValue) {
 
-    binA <- veupathUtils::Bin(binLabel=groupAValue)
-    binB <- veupathUtils::Bin(binLabel=groupBValue)
+    binA <- mbioUtils::Bin(binLabel=groupAValue)
+    binB <- mbioUtils::Bin(binLabel=groupBValue)
 
-    groupABins <- veupathUtils::BinList(S4Vectors::SimpleList(c(binA)))
-    groupBBins <- veupathUtils::BinList(S4Vectors::SimpleList(c(binB)))
+    groupABins <- mbioUtils::BinList(S4Vectors::SimpleList(c(binA)))
+    groupBBins <- mbioUtils::BinList(S4Vectors::SimpleList(c(binB)))
 
     comparatorVariable <- microbiomeComputations::Comparator(
-                            variable = veupathUtils::VariableMetadata(
+                            variable = mbioUtils::VariableMetadata(
                                 variableSpec = VariableSpec(
                                     variableId = covariate,
                                     entityId = ''
                                 ),
-                                dataShape = veupathUtils::DataShape(value="CATEGORICAL")
+                                dataShape = mbioUtils::DataShape(value="CATEGORICAL")
                             ),
                             groupA = groupABins,
                             groupB = groupBBins
@@ -156,8 +156,8 @@ function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verb
 #' @aliases differentialAbundance,CollectionWithMetadata,character,missingOrNULL,missingOrNULL-method
 setMethod("differentialAbundance", signature("CollectionWithMetadata", "character", "missingOrNULL", "missingOrNULL"), 
 function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verbose = c(TRUE, FALSE)) {
-    method <- veupathUtils::matchArg(method)
-    verbose <- veupathUtils::matchArg(verbose)
+    method <- mbioUtils::matchArg(method)
+    verbose <- mbioUtils::matchArg(verbose)
 
     if (data.table::uniqueN(data@sampleMetadata@data[[covariate]]) < 2) {
         stop("Argument 'covariate' must have at least two unique values")
@@ -176,8 +176,8 @@ function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verb
 #' @aliases differentialAbundance,CollectionWithMetadata,character,function,missingOrNULL-method
 setMethod("differentialAbundance", signature("CollectionWithMetadata", "character", "function", "missingOrNULL"),
 function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verbose = c(TRUE, FALSE)) {
-    method <- veupathUtils::matchArg(method)
-    verbose <- veupathUtils::matchArg(verbose)
+    method <- mbioUtils::matchArg(method)
+    verbose <- mbioUtils::matchArg(verbose)
 
     if (data.table::uniqueN(data@sampleMetadata@data[[covariate]]) < 2) {
         stop("Argument 'covariate' must have at least two unique values")
@@ -193,8 +193,8 @@ function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verb
 #' @aliases differentialAbundance,CollectionWithMetadata,character,character,missingOrNULL-method
 setMethod("differentialAbundance", signature("CollectionWithMetadata", "character", "character", "missingOrNULL"),
 function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verbose = c(TRUE, FALSE)) {
-    method <- veupathUtils::matchArg(method)
-    verbose <- veupathUtils::matchArg(verbose)
+    method <- mbioUtils::matchArg(method)
+    verbose <- mbioUtils::matchArg(verbose)
 
     covariateDataType <- class(data@sampleMetadata@data[[covariate]])
     if (!covariateDataType %in% c("factor", "character")) {
@@ -215,8 +215,8 @@ function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verb
 #' @aliases differentialAbundance,CollectionWithMetadata,character,function,function-method
 setMethod("differentialAbundance", signature("CollectionWithMetadata", "character", "function", "function"),
 function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verbose = c(TRUE, FALSE)) {
-    method <- veupathUtils::matchArg(method)
-    verbose <- veupathUtils::matchArg(verbose)
+    method <- mbioUtils::matchArg(method)
+    verbose <- mbioUtils::matchArg(verbose)
 
     if (data.table::uniqueN(data@sampleMetadata@data[[covariate]]) < 2) {
         stop("Argument 'covariate' must have at least two unique values")
@@ -233,8 +233,8 @@ function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verb
 #' @aliases differentialAbundance,CollectionWithMetadata,character,character,character-method
 setMethod("differentialAbundance", signature("CollectionWithMetadata", "character", "character", "character"),
 function(data, covariate, groupA, groupB, method = c("Maaslin2", "DESeq2"), verbose = c(TRUE, FALSE)) {
-    method <- veupathUtils::matchArg(method)
-    verbose <- veupathUtils::matchArg(verbose)
+    method <- mbioUtils::matchArg(method)
+    verbose <- mbioUtils::matchArg(verbose)
 
     covariateDataType <- class(data@sampleMetadata@data[[covariate]])
     if (!covariateDataType %in% c("factor", "character")) {
@@ -297,12 +297,12 @@ setGeneric("Maaslin2", function(data, verbose = c(TRUE,FALSE), ...) standardGene
 #' @rdname Maaslin2
 #' @aliases Maaslin2,CollectionWithMetadata-method
 setMethod("Maaslin2", signature("CollectionWithMetadata"), function(data, verbose = c(TRUE,FALSE), ...) {
-    verbose <- veupathUtils::matchArg(verbose)
+    verbose <- mbioUtils::matchArg(verbose)
 
     recordIdColumn <- data@recordIdColumn
     ancestorIdColumns <- data@ancestorIdColumns
     allIdColumns <- c(recordIdColumn, ancestorIdColumns)
-    sampleMetadata <- veupathUtils::getSampleMetadata(data)
+    sampleMetadata <- mbioUtils::getSampleMetadata(data)
     abundances <- microbiomeComputations::getAbundances(data)
 
     # remove rows in sampleMetadata where covariate is NA or empty string
@@ -353,12 +353,12 @@ setGeneric("DESeqDataSetFromCollection", function(data, verbose = c(TRUE,FALSE),
 #' @rdname DESeqDataSetFromCollection
 #' @aliases DESeqDataSetFromCollection,AbsoluteAbundanceData-method
 setMethod("DESeqDataSetFromCollection", signature("AbsoluteAbundanceData"), function(data, verbose = c(TRUE,FALSE), ...) {
-    verbose <- veupathUtils::matchArg(verbose)
+    verbose <- mbioUtils::matchArg(verbose)
 
     recordIdColumn <- data@recordIdColumn
     ancestorIdColumns <- data@ancestorIdColumns
     allIdColumns <- c(recordIdColumn, ancestorIdColumns)
-    sampleMetadata <- veupathUtils::getSampleMetadata(data)
+    sampleMetadata <- mbioUtils::getSampleMetadata(data)
     abundances <- microbiomeComputations::getAbundances(data, verbose = verbose)
 
     # First, remove id columns and any columns that are all 0s.
@@ -375,7 +375,7 @@ setMethod("DESeqDataSetFromCollection", signature("AbsoluteAbundanceData"), func
     # expects the order to match, and will not perform this check.
     if (!identical(rownames(sampleMetadata), colnames(counts))){
         # Reorder sampleMetadata to match counts
-        veupathUtils::logWithTime("Sample order differs between data and metadata. Reordering data based on the metadata sample order.", verbose)
+        mbioUtils::logWithTime("Sample order differs between data and metadata. Reordering data based on the metadata sample order.", verbose)
         data.table::setcolorder(counts, rownames(sampleMetadata))
     }
 

R/methods-ComputeResult.R

@@ -17,7 +17,7 @@
 #' @param format The format of the compute result. Currently only "data.table" and "igraph" are supported.
 #' @param ... additional arguments passed to getComputeResult method of the subclasses of ComputeResult
 #' @return The compute result in the specified format
-#' @importFrom veupathUtils matchArg ComputeResult
+#' @importFrom mbioUtils matchArg ComputeResult
 #' @export
 #' @rdname getComputeResult
 setGeneric("getComputeResult", function(object, format = c("data.table"), ...) standardGeneric("getComputeResult"))
@@ -26,7 +26,7 @@ setGeneric("getComputeResult", function(object, format = c("data.table"), ...) s
 #' @rdname getComputeResult
 #' @aliases getComputeResult,ComputeResult-method
 setMethod("getComputeResult", "ComputeResult", function(object, format = c("data.table", "igraph"), ...) {
-    format <- veupathUtils::matchArg(format)
+    format <- mbioUtils::matchArg(format)
 
     if (!!length(object@statistics)) {
         return(getComputeResult(object@statistics, format, ...))
@@ -41,15 +41,15 @@ setMethod("getComputeResult", "ComputeResult", function(object, format = c("data
     return(dt)  
 })
 
-#' @importFrom veupathUtils CorrelationResult
+#' @importFrom mbioUtils CorrelationResult
 #' @rdname getComputeResult
 #' @param correlationCoefThreshold threshold to filter edges by correlation coefficient. 
 #' Edges with correlation coefficients below this threshold will be removed. Default is .5
 #' @param pValueThreshold threshold to filter edges by p-value. Edges with p-values above this threshold will be removed. Default is .05
 #' @aliases getComputeResult,CorrelationResult-method
 #' @importFrom igraph graph_from_data_frame
 setMethod("getComputeResult", "CorrelationResult", function(object, format = c("data.table", "igraph"), correlationCoefThreshold = .5, pValueThreshold = .05) {
-    format <- veupathUtils::matchArg(format)
+    format <- mbioUtils::matchArg(format)
 
     result <- data.table::setDT(object@statistics)
 
@@ -66,17 +66,17 @@ setMethod("getComputeResult", "CorrelationResult", function(object, format = c("
 #' @rdname getComputeResult
 #' @aliases getComputeResult,DifferentialAbundanceResult-method
 setMethod("getComputeResult", "DifferentialAbundanceResult", function(object, format = c("data.table")) {
-    format <- veupathUtils::matchArg(format) 
+    format <- mbioUtils::matchArg(format) 
     return(data.table::setDT(object@statistics))
 })
 
-#' @importFrom veupathUtils getSampleMetadata
-#' @importFrom veupathUtils getSampleMetadataIdColumns
+#' @importFrom mbioUtils getSampleMetadata
+#' @importFrom mbioUtils getSampleMetadataIdColumns
 mergeComputeResultAndMetadata <- function(computeResult, dataset, metadataVariables) {
     dt <- getComputeResult(computeResult, "data.table")
-    metadata <- veupathUtils::getSampleMetadata(dataset, includeIds = TRUE, metadataVariables = metadataVariables)
+    metadata <- mbioUtils::getSampleMetadata(dataset, includeIds = TRUE, metadataVariables = metadataVariables)
 
-    metadataIdColumns <- veupathUtils::getSampleMetadataIdColumns(dataset)
+    metadataIdColumns <- mbioUtils::getSampleMetadataIdColumns(dataset)
     dt <- merge(dt, metadata, by = metadataIdColumns, all.x = TRUE)
 
     return(dt)
@@ -117,7 +117,7 @@ function(object, dataset, format = c("data.table"), metadataVariables = NULL)
 #' @aliases getComputeResultWithMetadata,ComputeResult,MbioDataset-method
 setMethod("getComputeResultWithMetadata", signature = c("ComputeResult", "MbioDataset"), 
 function(object, dataset = NULL, format = c("data.table"), metadataVariables = NULL) {
-    format <- veupathUtils::matchArg(format)
+    format <- mbioUtils::matchArg(format)
     dt <- mergeComputeResultAndMetadata(object, dataset, metadataVariables)
 
     return(dt)
@@ -127,7 +127,7 @@ function(object, dataset = NULL, format = c("data.table"), metadataVariables = N
 #' @aliases getComputeResultWithMetadata,ComputeResult,Collection-method
 setMethod("getComputeResultWithMetadata", signature = c("ComputeResult", "Collection"), 
 function(object, dataset = NULL, format = c("data.table"), metadataVariables = NULL) {
-    format <- veupathUtils::matchArg(format)
+    format <- mbioUtils::matchArg(format)
     dt <- mergeComputeResultAndMetadata(object, dataset, metadataVariables)
 
     return(dt)
@@ -137,7 +137,7 @@ function(object, dataset = NULL, format = c("data.table"), metadataVariables = N
 #' @aliases getComputeResultWithMetadata,ComputeResult,AbundanceData-method
 setMethod("getComputeResultWithMetadata", signature = c("ComputeResult", "AbundanceData"), 
 function(object, dataset = NULL, format = c("data.table"), metadataVariables = NULL) {
-    format <- veupathUtils::matchArg(format)
+    format <- mbioUtils::matchArg(format)
     dt <- mergeComputeResultAndMetadata(object, dataset, metadataVariables)
 
     return(dt)
@@ -196,7 +196,7 @@ setMethod("correlationNetwork", "data.frame", function(
     pValueThreshold = .05, 
     bipartiteNetwork = c(FALSE, TRUE)
 ) {
-    bipartiteNetwork <- veupathUtils::matchArg(bipartiteNetwork)
+    bipartiteNetwork <- mbioUtils::matchArg(bipartiteNetwork)
 
     warning("data.frame input assumes the columns are in the following order: source, target, correlationCoef, pValue.")
     names(object) <- c("source", "target", "value", "pValue")