deprecate Taxa names -> Features

NAMESPACE

@@ -4,6 +4,7 @@ export(plotAbundanceDensity)
 export(plotColGraph)
 export(plotColTile)
 export(plotDMNFit)
+export(plotFeaturePrevalence)
 export(plotPrevalence)
 export(plotPrevalentAbundance)
 export(plotRowGraph)
@@ -20,6 +21,7 @@ exportMethods(plotColGraph)
 exportMethods(plotColTile)
 exportMethods(plotColTree)
 exportMethods(plotDMNFit)
+exportMethods(plotFeaturePrevalence)
 exportMethods(plotPrevalence)
 exportMethods(plotPrevalentAbundance)
 exportMethods(plotRowGraph)

R/plotAbundance.R

@@ -112,7 +112,7 @@
 #' # Getting top taxa on a Phylum level
 #' se <- transformAssay(se, method="relabundance")
 #' se_phylum <- agglomerateByRank(se, rank ="Phylum", onRankOnly=TRUE)
-#' top_taxa <- getTopTaxa(se_phylum,top = 5, assay.type = "relabundance")
+#' top_taxa <- getTopFeatures(se_phylum,top = 5, assay.type = "relabundance")
 #' 
 #' # Renaming the "Phylum" rank to keep only top taxa and the rest to "Other"
 #' phylum_renamed <- lapply(rowData(se)$Phylum,

R/plotPrevalence.R

@@ -1,9 +1,9 @@
 #' Plot prevalence information
 #' 
-#' \code{plotPrevalence} and \code{plotTaxaPrevalence} visualize prevalence 
+#' \code{plotPrevalence} and \code{plotFeaturePrevalence} visualize prevalence 
 #' information.
 #' 
-#' Whereas \code{plotPrevalence} produces a line plot, \code{plotTaxaPrevalence}
+#' Whereas \code{plotPrevalence} produces a line plot, \code{plotFeaturePrevalence}
 #' returns a heatmap. 
 #' 
 #' @param x a
@@ -100,14 +100,14 @@
 #' plotPrevalence(GlobalPatterns, rank = "Phylum") + scale_x_log10()
 #' 
 #' # plotting prevalence per taxa for different detection thresholds as heatmap
-#' plotTaxaPrevalence(GlobalPatterns, rank = "Phylum")
+#' plotFeaturePrevalence(GlobalPatterns, rank = "Phylum")
 #' 
 #' # by default a continuous scale is used for different detection levels, 
 #' # but this can be adjusted
-#' plotTaxaPrevalence(GlobalPatterns, rank = "Phylum",
+#' plotFeaturePrevalence(GlobalPatterns, rank = "Phylum",
 #'                    detections = c(0, 0.001, 0.01, 0.1, 0.2))
 #'                    
-#' # point layout for plotTaxaPrevalence can be used to visualize by additional
+#' # point layout for plotFeaturePrevalence can be used to visualize by additional
 #' # information
 #' plotPrevalentAbundance(GlobalPatterns, rank = "Family",
 #'                        colour_by = "Phylum") +
@@ -337,16 +337,17 @@ setMethod("plotPrevalentAbundance", signature = c(x = "SummarizedExperiment"),
 }
 
 ################################################################################
-# plotTaxaPrevalence
+# plotFeaturePrevalence
 
 #' @rdname plotPrevalence
+#' @aliases plotTaxaPrevalence
 #' @export
-setGeneric("plotTaxaPrevalence", signature = c("x"),
-           function(x, ...) standardGeneric("plotTaxaPrevalence"))
+setGeneric("plotFeaturePrevalence", signature = c("x"),
+           function(x, ...) standardGeneric("plotFeaturePrevalence"))
 
 #' @rdname plotPrevalence
 #' @export
-setMethod("plotTaxaPrevalence", signature = c(x = "SummarizedExperiment"),
+setMethod("plotFeaturePrevalence", signature = c(x = "SummarizedExperiment"),
           function(x,
                    rank = taxonomyRanks(x)[1L],
                    assay.type = assay_name, assay_name = "counts",
@@ -542,3 +543,20 @@ setMethod("plotTaxaPrevalence", signature = c(x = "SummarizedExperiment"),
                            angle_x_text = FALSE)
     plot_out
 }
+
+#' @rdname plotPrevalence
+#' @aliases plotFeaturePrevalence
+#' @export
+setGeneric("plotTaxaPrevalence", signature = c("x"),
+           function(x, ...) 
+             standardGeneric("plotTaxaPrevalence"))
+
+#' @rdname plotPrevalence
+#' @aliases plotFeaturePrevalence
+#' @export
+setMethod("plotTaxaPrevalence", signature = c(x = "ANY"),
+          function(x, ...){
+            .Deprecated(old ="plotTaxaPrevalence", new = "plotFeaturePrevalence", msg = "The 'plotTaxaPrevalence' function is deprecated. Use 'plotFeaturePrevalence' instead.")
+            plotFeaturePrevalence(x, ...)
+          }
+)

R/plotSeries.R

@@ -63,7 +63,7 @@
 #' # Plots 2 most abundant taxa, which are colored by their family
 #' plotSeries(object,
 #'            x = "DAY_ORDER",
-#'            y = getTopTaxa(object, 2),
+#'            y = getTopFeatures(object, 2),
 #'            colour_by = "Family")
 #' 
 #' # Counts relative abundances
@@ -82,7 +82,7 @@
 #' # In addition to 'colour_by' and 'linetype_by', 'size_by' can also be used to group taxa.
 #' plotSeries(object,
 #'            x = "DAY_ORDER", 
-#'            y = getTopTaxa(object, 5), 
+#'            y = getTopFeatures(object, 5), 
 #'            colour_by = "Family",
 #'            size_by = "Phylum",
 #'            assay.type = "counts")

R/plotTree.R

@@ -112,7 +112,7 @@
 #'   log(rowData(altExp(GlobalPatterns,"Genus"))$mean)
 #' rowData(altExp(GlobalPatterns,"Genus"))$detected <-
 #'    rowData(altExp(GlobalPatterns,"Genus"))$detected / 100
-#' top_genus <- getTopTaxa(altExp(GlobalPatterns,"Genus"),
+#' top_genus <- getTopFeatures(altExp(GlobalPatterns,"Genus"),
 #'                         method="mean",
 #'                         top=100L,
 #'                         assay.type="counts")
@@ -149,7 +149,7 @@
 #' # please note that the original tree of GlobalPatterns is dropped by
 #' # unsplitByRanks
 #' altExps(GlobalPatterns) <- splitByRanks(GlobalPatterns)
-#' top_phyla <- getTopTaxa(altExp(GlobalPatterns,"Phylum"),
+#' top_phyla <- getTopFeatures(altExp(GlobalPatterns,"Phylum"),
 #'                         method="mean",
 #'                         top=10L,
 #'                         assay.type="counts")

vignettes/miaViz.Rmd

@@ -73,7 +73,7 @@ plotAbundance(GlobalPatterns, rank = "Kingdom", assay.type = "relabundance")
 With subsetting to selected features the plot can be fine tuned.
 
 ```{r}
-prev_phylum <- getPrevalentTaxa(GlobalPatterns, rank = "Phylum",
+prev_phylum <- getPrevalentFeatures(GlobalPatterns, rank = "Phylum",
                                 detection = 0.01)
 ```
 
@@ -103,14 +103,14 @@ Further example about composition barplot can be found at Orchestrating Microbio
 # Prevalence plotting
 
 To visualize prevalence within the dataset, two functions are available,
-`plotTaxaPrevalence`, `plotPrevalenceAbundance` and `plotPrevalence`.
+`plotFeaturePrevalence`, `plotPrevalenceAbundance` and `plotPrevalence`.
 
 
-`plotTaxaPrevalence` produces a so-called landscape plot, which
+`plotFeaturePrevalence` produces a so-called landscape plot, which
 visualizes the prevalence of samples across abundance thresholds.
 
 ```{r}
-plotTaxaPrevalence(GlobalPatterns, rank = "Phylum",
+plotFeaturePrevalence(GlobalPatterns, rank = "Phylum",
                    detections = c(0, 0.001, 0.01, 0.1, 0.2))
 ```
 
@@ -155,7 +155,7 @@ rowData(altExp(GlobalPatterns,"Genus"))$log_mean <-
     log(rowData(altExp(GlobalPatterns,"Genus"))$mean)
 rowData(altExp(GlobalPatterns,"Genus"))$detected <- 
     rowData(altExp(GlobalPatterns,"Genus"))$detected / 100
-top_taxa <- getTopTaxa(altExp(GlobalPatterns,"Genus"),
+top_taxa <- getTopFeatures(altExp(GlobalPatterns,"Genus"),
                        method="mean",
                        top=100L,
                        assay.type="counts")
@@ -262,7 +262,7 @@ library("miaTime")
 data(SilvermanAGutData, package="miaTime")
 tse <- SilvermanAGutData
 tse <- transformAssay(tse, method = "relabundance")
-taxa <- getTopTaxa(tse, 2)
+taxa <- getTopFeatures(tse, 2)
 ```
 
 Data from samples collected along time can be visualized using `plotSeries`.
@@ -294,7 +294,7 @@ Additional variables can be used to modify line type aesthetics.
 ```{r}
 plotSeries(tse,
            x = "DAY_ORDER",
-           y = getTopTaxa(tse, 5),
+           y = getTopFeatures(tse, 5),
            colour_by = "Family",
            linetype_by = "Phylum",
            assay.type = "counts")