diff --git a/DESCRIPTION b/DESCRIPTION
index 0ccb87d9..533fa8ee 100644
--- a/DESCRIPTION
+++ b/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 = "tuomas.v.borman@utu.fi",
diff --git a/NEWS b/NEWS
index 5931bea2..8fa8af51 100644
--- a/NEWS
+++ b/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 
diff --git a/R/plotTree.R b/R/plotTree.R
index d1fc0d52..5d066bf7 100644
--- a/R/plotTree.R
+++ b/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,
diff --git a/man/plotTree.Rd b/man/plotTree.Rd
index 5790a767..72903efe 100644
--- a/man/plotTree.Rd
+++ b/man/plotTree.Rd
@@ -167,7 +167,7 @@ library(scater)
 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)
@@ -209,7 +209,7 @@ plotRowTree(x[rownames(x) \%in\% top_genus,],
 # 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,
@@ -241,5 +241,5 @@ plotRowTree(x[rowData(x)$Phylum \%in\% top_phyla,],
             node_colour_by = "log_mean")
 }
 \seealso{
-\code{\link[mia:splitByRanks]{splitByRanks}}
+\code{\link[mia:agglomerate-methods]{agglomerateByRanks}}
 }