Update uniqueness_gtest output, remove datadr and trelliscope

DESCRIPTION

@@ -33,17 +33,15 @@ Imports:
     readr
 Suggests:
     MetaCycData,
-    datadr,
     knitr,
     rmarkdown,
     foreach,
     doParallel,
     testthat,
     purrr,
-    viridis,
-    DT
+    DT,
+    hexbin
 Remotes:
-    github::delta-rho/datadr,
     github::EMSL-Computing/MetaCycData
 VignetteBuilder: knitr
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2

NAMESPACE

@@ -38,7 +38,6 @@ export(compound_calcs)
 export(concat)
 export(conf_filter)
 export(coreMSDataToFtmsData)
-export(densityCognostics)
 export(densityPlot)
 export(divideByGroup)
 export(divideByGroupComparisons)
@@ -95,7 +94,6 @@ export(getSulfurColName)
 export(getVanKrevelenCategoryBounds)
 export(group_designation)
 export(heatmap)
-export(kendrickCognostics)
 export(kendrickPlot)
 export(mapCompoundsToModules)
 export(mapCompoundsToReactions)
@@ -104,7 +102,6 @@ export(mass_error_plot)
 export(mass_filter)
 export(molecule_filter)
 export(numPeaksPlot)
-export(panelFunctionGenerator)
 export(parseModuleReaction)
 export(plotPrincipalCoordinates)
 export(plotlyHeatmap)
@@ -114,7 +111,6 @@ export(summarizeGroupComparisons)
 export(summarizeGroups)
 export(transformation_counts)
 export(unique_mf_assignment)
-export(vanKrevelenCognostics)
 export(vanKrevelenPlot)
 importFrom(dplyr,"%>%")
 importFrom(magrittr,"%>%")

R/concat.R

@@ -1,47 +1,42 @@
-#' Combine multiple distributed data objects of ftmsData
+#' Combine multiple ftmsData objects
 #' 
-#' Combine multiple distributed data objects (ddo) into a single ddo
+#' Combine multiple ftmsData objects into a single ftmsData object
 #' for further analysis or visualizations. The inputs to this function are
-#' the ddo objects created by \code{\link{divideByGroup}} or 
-#' \code{\link{divideByGroupComparisons}}. The output is a new ddo
+#' the ftmsData objects created by \code{\link{divideByGroup}} or 
+#' \code{\link{divideByGroupComparisons}}. The output is a new ftmsData
 #' with all the data of the supplied inputs, in a form that can be 
 #' summarized with \code{\link{summarizeGroups}} or \code{\link{summarizeGroupComparisons}}
-#' respectively, or visualized with \code{trelliscope}.
+#' respectively.
 #' 
-#' @param ... two or more ddo objects that are the output of \code{\link{summarizeGroups}} or \code{\link{summarizeGroupComparisons}}
+#' @param ... two or more ftmsData objects that are the output of \code{\link{summarizeGroups}} or \code{\link{summarizeGroupComparisons}}
 #' 
-#' @seealso \link[datadr:ddo]{ddo}
 #' @author Amanda White
 #' 
 #' @export
 #' 
 #' @examples 
 #' data("exampleProcessedPeakData")
 #' exampleProcessedPeakData <- group_designation(exampleProcessedPeakData, main_effects = "Location")
-#' grpDdo1 <- divideByGroup(exampleProcessedPeakData)
+#' grp1 <- divideByGroup(exampleProcessedPeakData)
 #' 
 #' exampleProcessedPeakData <- group_designation(exampleProcessedPeakData, main_effects = "Crop.Flora")
-#' grpDdo2 <- divideByGroup(exampleProcessedPeakData)
+#' grp2 <- divideByGroup(exampleProcessedPeakData)
 #' 
-#' allGrpDdo <-concat(grpDdo1, grpDdo2)
-#' grpSummaries <- summarizeGroups(allGrpDdo, c("n_present", "prop_present"))
+#' allGrps <-concat(grp1, grp2)
+#' grpSummaries <- summarizeGroups(allGrps, c("n_present", "prop_present"))
 concat <- function(...) {
-  require(datadr)
-
   parms <- list(...)
   # test inputs
   if (length(parms) == 0) return(NULL)
-  if (!all(unlist(lapply(parms, function(x) inherits(x, "ddo"))))) 
-    stop("input values must be ddo objects")
-  if (!all(unlist(lapply(parms, function(x) inherits(x[[1]]$value, "ftmsData") | inherits(x[[1]]$value, "groupComparison"))))) 
-    stop("input values must be distributed data objects of ftmsData or groupComparison objects")
+  if (!all(unlist(lapply(parms, function(x) inherits(x, "list"))))) 
+    stop("input values must be list objects")
+  if (!all(unlist(lapply(parms, function(x) inherits(x[[1]], "ftmsData") | inherits(x[[1]], "groupComparison"))))) 
+    stop("input values must be lists of ftmsData or groupComparison objects")
 
   if (length(parms) == 1) return(parms[[1]])
 
-  # combine multiple DDOs
-  tmp <- unlist(lapply(parms, as.list), recursive = FALSE)
-  res <- ddo(tmp)
+  # combine multiple lists of ftmsData Objects
+  res <- c(unlist(parms, recursive=FALSE))
 
   return(res)
 }
-

R/divideByGroup.R

@@ -1,36 +1,34 @@
-#' Divide an ftmsData object by group to form a ddo
+#' Divide an ftmsData object by group to form a list of ftmsData objects
 #' 
-#' Construct a \code{\link[datadr:ddo]{ddo}} from an \code{ftmsData} object by dividing
-#' by group. The resulting object may be used with Trelliscope to make
-#' plots for each group. The input data must have a \code{group_DF} attribute
-#' defining the groups.
+#' Construct a list of subsetted ftmsData objects from an \code{ftmsData} object by dividing
+#' by group.
 #' 
 #' @param ftmsObj ftmsData object
-#' @return a ddo where each division is a subset of \code{ftmsObj} corresponding
+#' @return a list where each element is a subset of \code{ftmsObj} corresponding
 #'         to a single group
-#' @seealso \code{\link[datadr:ddo]{ddo}}
 #' @export
 divideByGroup <- function(ftmsObj) {
-  require(datadr)
   sample.colname <- getFDataColName(ftmsObj)
   samples <- as.character(ftmsObj$f_data[, sample.colname])
   groupDF <- getGroupDF(ftmsObj)
   if (is.null(groupDF)) stop("This object does not have group designation information")
-
+  
   edata_nonsample_cols <- setdiff(colnames(ftmsObj$e_data), samples)
 
   result <- lapply(unique(groupDF$Group), function(group_name) {
-
+    
     val <- subset(ftmsObj, groups=group_name)
 
-    # datadr attributes:
     attr(val, "split") <- data.frame(Group=group_name, stringsAsFactors = FALSE)
     colnames(attr(val, "split")) <- "Group"
 
-    key <- paste0("Group=", group_name)
-    return(kvPair(key, val))
+    return(val)
+  })
+
+  result_names <- lapply(unique(groupDF$Group), function(group_name) {
+    paste0("Group=", group_name)
   })
+  names(result) <- result_names
 
-  result <- ddo(result)
   return(result)
 }

R/divideByGroupComparisons.R

@@ -1,24 +1,23 @@
-#' Construct a ddo of group comparisons
+#' Construct a list of group comparisons
 #' 
-#' Construct a \code{\link[datadr:ddo]{ddo}} where each subset consists of data for
+#' Construct a list where each element is a subset consisting of data for
 #' a pair of groups. This is used to facilitate analysis and visualizations
 #' of group comparisons.
 #' 
 #' @param ftmsObj ftmsData object
 #' @param comparisons dictates which pairwise comparisons to make. 'all' will create a matrix for all pairwise comparisons, 'control' will create a matrix for all comparisons against a specified control group, 'one-factor' will create a matrix of pairwise comparisons to be made where only one 'main_effect' changes between the two groups, or a list of specific comparisons to be made (e.g., list(c("Group1","Group2"),c("Group3","Group4"))) can be given.
 #' @param control if wanting to only compare against a control, must specify which group or sample is the control
-#' @return a distributed data object where each division consists of a subset of \code{ftmsObj} with
+#' @return a named list where each element consists of a subset of \code{ftmsObj} with
 #' data from just two groups.
 #' @export
 divideByGroupComparisons <- function(ftmsObj, comparisons, control=NULL) {
+
   if (missing(ftmsObj)) stop("ftmsObj is missing")
   if (missing(comparisons)) stop("comparisons is missing")
   if (!inherits(ftmsObj, "ftmsData")) stop("ftmsObj must be of type ftmsData")
 #  if (!is.matrix(comparisons) & !is.data.frame(comparisons)) stop("comparisons must be either a matrix or a data frame")
   if (missing(comparisons)) stop("comparisons is missing")
 
-  require(datadr)  
-
   fdata.colname <- getFDataColName(ftmsObj)
 
   groupDF <- ftmsRanalysis:::getGroupDF(ftmsObj)
@@ -35,6 +34,7 @@ divideByGroupComparisons <- function(ftmsObj, comparisons, control=NULL) {
   samples <- unique(as.character(ftmsObj$f_data[, fdata.colname]))
   edata_nonsample_cols <- setdiff(colnames(ftmsObj$e_data), groups)
 
+  # lapply over each col in matrix and return list of subset data
   result <- lapply(1:ncol(compMatrix), function(i) {
     grp.names <- compMatrix[,i]
 
@@ -45,10 +45,19 @@ divideByGroupComparisons <- function(ftmsObj, comparisons, control=NULL) {
     attr(val, "split") <- data.frame(Group_Comparison=comp_name, stringsAsFactors = FALSE)
     colnames(attr(val, "split")) <- "Group_Comparison"
 
+    return(val)
+  })
+
+  # Loop over cols of matrix and create vector of names for results above
+  result_names <- lapply(1:ncol(compMatrix), function(i) {
+    grp.names <- compMatrix[,i]
+    comp_name <- paste(grp.names, collapse=" vs ")
     key <- paste0("Group_Comparison=", comp_name)
-    return(kvPair(key, val))
+    return(key)
   })
-  result <- ddo(result)
+
+  names(result) <- result_names
+
   attr(result, "e_meta") <- ftmsObj$e_meta
   return(result)
 }