replace splitByRanks with agglomerateByRanks (#115)

Co-authored-by: Tuomas Borman <[email protected]>

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: miaViz
 Title: Microbiome Analysis Plotting and Visualization
-Version: 1.13.2
+Version: 1.13.3
 Authors@R: 
     c(person(given = "Tuomas", family = "Borman", role = c("aut", "cre"),
              email = "[email protected]",

NEWS

@@ -27,4 +27,4 @@ Changes in version 1.11.x
 
 Changes in version 1.13.x
 + plot*Tree: bugfix, ununique nodes
-+ Added confidence.level parameter to plotCCA
++ Added confidence.level parameter to plotCCA 

R/plotTree.R

@@ -97,7 +97,7 @@
 #' @return a \code{\link{ggtree}} plot
 #' 
 #' @seealso
-#' \code{\link[mia:splitByRanks]{splitByRanks}}
+#' \code{\link[mia:agglomerate-methods]{agglomerateByRanks}}
 #'
 #' @name plotTree
 #'
@@ -106,7 +106,7 @@
 #' library(mia)
 #' # preparation of some data
 #' data(GlobalPatterns)
-#' altExps(GlobalPatterns) <- splitByRanks(GlobalPatterns)
+#' GlobalPatterns <- agglomerateByRanks(GlobalPatterns)
 #' altExp(GlobalPatterns,"Genus") <- addPerFeatureQC(altExp(GlobalPatterns,"Genus"))
 #' rowData(altExp(GlobalPatterns,"Genus"))$log_mean <-
 #'   log(rowData(altExp(GlobalPatterns,"Genus"))$mean)
@@ -148,7 +148,7 @@
 #' # aggregating data over the taxonomic levels for plotting a taxonomic tree
 #' # please note that the original tree of GlobalPatterns is dropped by
 #' # unsplitByRanks
-#' altExps(GlobalPatterns) <- splitByRanks(GlobalPatterns)
+#' GlobalPatterns <- agglomerateByRanks(GlobalPatterns)
 #' top_phyla <- getTopFeatures(altExp(GlobalPatterns,"Phylum"),
 #'                         method="mean",
 #'                         top=10L,