diff --git a/DESCRIPTION b/DESCRIPTION
index 770648ef..541968ad 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -14,7 +14,8 @@ Authors@R:
       person(given = "Basil", family = "Courbayre", role = c("ctb")),
       person(given = "Giulio", family = "Benedetti", role = c("ctb"),
              email = "giulio.benedetti@utu.fi",
-             comment = c(ORCID = "0000-0002-8732-7692"))
+             comment = c(ORCID = "0000-0002-8732-7692")),
+      person(given = "Muluh", family = "Muluh", role=c("ctb"))
 	     )
 Description: The miaViz package implements functions to visualize
     TreeSummarizedExperiment objects especially in the context of microbiome
diff --git a/NEWS b/NEWS
index b584ddb0..eee544a5 100644
--- a/NEWS
+++ b/NEWS
@@ -21,6 +21,7 @@ Changes in version 1.7.x
 Changes in version 1.9.x
 + Updated plotDMN to work with newest mia version
 + Added plotCCA and plotRDA functions
++ deprecate agglomerateByRank and agglomerateByPrevalence
 
 Changes in version 1.11.x
 + replace addTaxonomyTree with addHierarchyTree after renaming in mia package
diff --git a/R/plotGraph.R b/R/plotGraph.R
index 133c7f9b..93a2ff10 100644
--- a/R/plotGraph.R
+++ b/R/plotGraph.R
@@ -88,9 +88,9 @@
 #' data(row_graph_order)
 #' metadata(GlobalPatterns)$col_graph <- col_graph
 #' 
-#' genus <- agglomerateByRank(GlobalPatterns,"Genus",na.rm=TRUE)
+#' genus <- mergeFeaturesByRank(GlobalPatterns,"Genus",na.rm=TRUE)
 #' metadata(genus)$row_graph <- row_graph
-#' order <- agglomerateByRank(genus,"Order",na.rm=TRUE)
+#' order <- mergeFeaturesByRank(genus,"Order",na.rm=TRUE)
 #' metadata(order)$row_graph <- row_graph_order
 #' 
 #' # plot a graph independently
diff --git a/R/plotPrevalence.R b/R/plotPrevalence.R
index a67ea4b3..bf425c03 100644
--- a/R/plotPrevalence.R
+++ b/R/plotPrevalence.R
@@ -13,8 +13,8 @@
 #' @param rank,... additional arguments
 #' \itemize{
 #'   \item{If \code{!is.null(rank)} matching arguments are passed on to
-#'     \code{\link[=agglomerate-methods]{agglomerateByRank}}. See
-#'     \code{\link[=agglomerate-methods]{?agglomerateByRank}} for more details.
+#'     \code{\link[=agglomerate-methods]{mergeFeaturesByRank}}. See
+#'     \code{\link[=agglomerate-methods]{?mergeFeaturesByRank}} for more details.
 #'   }
 #'   \item{additional arguments for plotting. See 
 #'   \code{\link{mia-plot-args}} for more details i.e. call \code{help("mia-plot-args")}}
@@ -79,7 +79,7 @@
 #' 
 #' To exclude certain taxa, preprocess \code{x} to your liking, for example 
 #' with subsetting via \code{getPrevalentTaxa} or 
-#' \code{agglomerateByPrevalence}.
+#' \code{mergeFeaturesByPrevalence}.
 #' 
 #' @return 
 #' A \code{ggplot2} object or \code{plotly} object, if more than one 
@@ -87,8 +87,8 @@
 #' 
 #' @seealso 
 #' \code{\link[mia:getPrevalence]{getPrevalence}},
-#' \code{\link[mia:getPrevalence]{agglomerateByPrevalence}},
-#' \code{\link[mia:agglomerate-methods]{agglomerateByRank}}
+#' \code{\link[mia:getPrevalence]{mergeFeaturesByPrevalence}},
+#' \code{\link[mia:agglomerate-methods]{mergeFeaturesByRank}}
 #' 
 #' @name plotPrevalence
 #' 
diff --git a/R/plotSeries.R b/R/plotSeries.R
index 5b3eae12..18f9c89c 100644
--- a/R/plotSeries.R
+++ b/R/plotSeries.R
@@ -134,7 +134,7 @@ setMethod("plotSeries", signature = c(object = "SummarizedExperiment"),
             .check_taxonomic_rank(rank, object)
             
             # Agglomerates the object
-            object <- agglomerateByRank(object, rank = rank)
+            object <- mergeFeaturesByRank(object, rank = rank)
         }
         
         # Checks Y
diff --git a/man/plotGraph.Rd b/man/plotGraph.Rd
index 749a3acb..8401eeb6 100644
--- a/man/plotGraph.Rd
+++ b/man/plotGraph.Rd
@@ -142,9 +142,9 @@ data(row_graph)
 data(row_graph_order)
 metadata(GlobalPatterns)$col_graph <- col_graph
 
-genus <- agglomerateByRank(GlobalPatterns,"Genus",na.rm=TRUE)
+genus <- mergeFeaturesByRank(GlobalPatterns,"Genus",na.rm=TRUE)
 metadata(genus)$row_graph <- row_graph
-order <- agglomerateByRank(genus,"Order",na.rm=TRUE)
+order <- mergeFeaturesByRank(genus,"Order",na.rm=TRUE)
 metadata(order)$row_graph <- row_graph_order
 
 # plot a graph independently
diff --git a/man/plotPrevalence.Rd b/man/plotPrevalence.Rd
index 0884ae88..69e85ce0 100644
--- a/man/plotPrevalence.Rd
+++ b/man/plotPrevalence.Rd
@@ -88,8 +88,8 @@ on compositional (relative) abundances? Passed onto
 \item{rank, ...}{additional arguments
 \itemize{
 \item{If \code{!is.null(rank)} matching arguments are passed on to
-\code{\link[=agglomerate-methods]{agglomerateByRank}}. See
-\code{\link[=agglomerate-methods]{?agglomerateByRank}} for more details.
+\code{\link[=agglomerate-methods]{mergeFeaturesByRank}}. See
+\code{\link[=agglomerate-methods]{?mergeFeaturesByRank}} for more details.
 }
 \item{additional arguments for plotting. See
 \code{\link{mia-plot-args}} for more details i.e. call \code{help("mia-plot-args")}}
@@ -147,7 +147,7 @@ Agglomeration on different taxonomic levels is available through the
 
 To exclude certain taxa, preprocess \code{x} to your liking, for example
 with subsetting via \code{getPrevalentTaxa} or
-\code{agglomerateByPrevalence}.
+\code{mergeFeaturesByPrevalence}.
 }
 \examples{
 data(GlobalPatterns, package = "mia")
@@ -178,6 +178,6 @@ plotPrevalentAbundance(GlobalPatterns, rank = "Family",
 }
 \seealso{
 \code{\link[mia:getPrevalence]{getPrevalence}},
-\code{\link[mia:getPrevalence]{agglomerateByPrevalence}},
-\code{\link[mia:agglomerate-methods]{agglomerateByRank}}
+\code{\link[mia:getPrevalence]{mergeFeaturesByPrevalence}},
+\code{\link[mia:agglomerate-methods]{mergeFeaturesByRank}}
 }
diff --git a/tests/testthat/test-2plotGraph.R b/tests/testthat/test-2plotGraph.R
index d2bc6462..5ebaadcc 100644
--- a/tests/testthat/test-2plotGraph.R
+++ b/tests/testthat/test-2plotGraph.R
@@ -50,7 +50,7 @@ test_that("plot graph", {
     expect_equal(miaViz:::.colnames_tbl_graph(actual,"edges"),
                  c("from","to","weight"))
     #
-    genus <- agglomerateByRank(GlobalPatterns,"Genus",na.rm=TRUE)
+    genus <- mergeFeaturesByRank(GlobalPatterns,"Genus",na.rm=TRUE)
     plot <- plotColGraph(col_graph,
                          genus,
                          colour_by = "SampleType",
diff --git a/tests/testthat/test-2plotTree.R b/tests/testthat/test-2plotTree.R
index be96472c..2fbd1841 100644
--- a/tests/testthat/test-2plotTree.R
+++ b/tests/testthat/test-2plotTree.R
@@ -58,7 +58,7 @@ test_that("plot tree", {
     library(scater)
     library(mia)
     data(GlobalPatterns)
-    altExp(GlobalPatterns,"genus") <- agglomerateByRank(GlobalPatterns,"Genus", make_unique = FALSE)
+    altExp(GlobalPatterns,"genus") <- mergeFeaturesByRank(GlobalPatterns,"Genus", make_unique = FALSE)
     altExp(GlobalPatterns,"genus") <- addPerFeatureQC(altExp(GlobalPatterns,"genus"))
     rowData(altExp(GlobalPatterns,"genus"))$log_mean <- log(rowData(altExp(GlobalPatterns,"genus"))$mean)
     top_taxa <- getTopFeatures(altExp(GlobalPatterns,"genus"),
diff --git a/vignettes/miaViz.Rmd b/vignettes/miaViz.Rmd
index 1159cc64..1916dd4c 100644
--- a/vignettes/miaViz.Rmd
+++ b/vignettes/miaViz.Rmd
@@ -149,7 +149,7 @@ library(scater)
 library(mia)
 ```
 ```{r}
-altExp(GlobalPatterns,"Genus") <- agglomerateByRank(GlobalPatterns,"Genus")
+altExp(GlobalPatterns,"Genus") <- mergeFeaturesByRank(GlobalPatterns,"Genus")
 altExp(GlobalPatterns,"Genus") <- addPerFeatureQC(altExp(GlobalPatterns,"Genus"))
 rowData(altExp(GlobalPatterns,"Genus"))$log_mean <-
     log(rowData(altExp(GlobalPatterns,"Genus"))$mean)