diff --git a/DESCRIPTION b/DESCRIPTION
index f5afd928..bfa52d17 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: miaViz
 Title: Microbiome Analysis Plotting and Visualization
-Version: 1.21.4
+Version: 1.21.5
 Authors@R: 
     c(person(given = "Tuomas", family = "Borman", role = c("aut", "cre"),
              email = "tuomas.v.borman@utu.fi",
diff --git a/R/plotAbundance.R b/R/plotAbundance.R
index 66290806..11610458 100644
--- a/R/plotAbundance.R
+++ b/R/plotAbundance.R
@@ -64,7 +64,7 @@
 #'   plot be spitted into facets? (Default: \code{FALSE})
 #'
 #'   \item \code{facet.cols}: \code{Logical scalar}. Should the columns in the
-#'   plot be spitted into facets? (Default: \code{FALSE})
+#'   plot be spitted into facets? (Default: \code{TRUE})
 #'
 #'   \item \code{ncol}: \code{Numeric scalar}. if facets are applied,
 #'   \code{ncol} defines many columns should be for plotting the different
@@ -72,7 +72,7 @@
 #'
 #'   \item \code{scales} \code{Character scalar}. Defines the behavior of the
 #'   scales of each facet. The value is passed into
-#'   \code{\link[ggplot2:facet_wrap]{facet_wrap}}. (Default: \code{"fixed"})
+#'   \code{\link[ggplot2:facet_wrap]{facet_wrap}}. (Default: \code{"free_x"})
 #' }
 #' See \code{\link{mia-plot-args}} for more details i.e. call
 #' \code{help("mia-plot-args")}
@@ -123,19 +123,13 @@
 #' plot <- plotAbundance(
 #'     tse, assay.type = "relabundance", group = "Phylum",
 #'     col.var = "SampleType")
-#' \donttest{
-#' # These two plots can be combined with wrap_plots function from patchwork
-#' # package
-#' library(patchwork)
-#' wrap_plots(plot, ncol = 1, heights = c(0.95, 0.05))
-#' }
 #'
-#' # Same plot as above but showing sample IDs as labels for the x axis on the
-#' # top plot. Moreover, we use facets.
+#' # Create a plot with sample grouping, and showing sample IDs as labels for
+#' # the x axis on the top plot.
 #' plot <- plotAbundance(
 #'     tse, assay.type = "relabundance",
 #'     group = "Phylum", col.var = "SampleType", add.legend = FALSE,
-#'     add.x.text = TRUE, facet.cols = TRUE, scales = "free_x") +
+#'     add.x.text = TRUE) +
 #'     theme(axis.text.x = element_text(angle = 90))
 #' plot
 #'
@@ -557,8 +551,8 @@ setMethod("plotAbundance", signature = c("SummarizedExperiment"), function(
 #' @importFrom stats formula
 .abund_plotter_incorporate_metadata <- function(
         plot_out, df, col.var = features, features = NULL,
-        facet.cols = FALSE, facet.rows = one.facet,
-        one.facet = one_facet, one_facet = FALSE, ncol = 2, scales = "fixed",
+        facet.cols = TRUE, facet.rows = one.facet,
+        one.facet = one_facet, one_facet = FALSE, ncol = 2, scales = "free_x",
         ...){
     # To disable "no visible binding for global variable" message in cmdcheck
     X <- NULL
diff --git a/man/plotAbundance.Rd b/man/plotAbundance.Rd
index 6a6444bf..d48ee599 100644
--- a/man/plotAbundance.Rd
+++ b/man/plotAbundance.Rd
@@ -62,7 +62,7 @@ decreasing or increasing fashion? (Default: \code{FALSE})
 plot be spitted into facets? (Default: \code{FALSE})
 
 \item \code{facet.cols}: \code{Logical scalar}. Should the columns in the
-plot be spitted into facets? (Default: \code{FALSE})
+plot be spitted into facets? (Default: \code{TRUE})
 
 \item \code{ncol}: \code{Numeric scalar}. if facets are applied,
 \code{ncol} defines many columns should be for plotting the different
@@ -70,7 +70,7 @@ facets. (Default: \code{2})
 
 \item \code{scales} \code{Character scalar}. Defines the behavior of the
 scales of each facet. The value is passed into
-\code{\link[ggplot2:facet_wrap]{facet_wrap}}. (Default: \code{"fixed"})
+\code{\link[ggplot2:facet_wrap]{facet_wrap}}. (Default: \code{"free_x"})
 }
 See \code{\link{mia-plot-args}} for more details i.e. call
 \code{help("mia-plot-args")}}
@@ -139,19 +139,13 @@ plotAbundance(
 plot <- plotAbundance(
     tse, assay.type = "relabundance", group = "Phylum",
     col.var = "SampleType")
-\donttest{
-# These two plots can be combined with wrap_plots function from patchwork
-# package
-library(patchwork)
-wrap_plots(plot, ncol = 1, heights = c(0.95, 0.05))
-}
 
-# Same plot as above but showing sample IDs as labels for the x axis on the
-# top plot. Moreover, we use facets.
+# Create a plot with sample grouping, and showing sample IDs as labels for
+# the x axis on the top plot.
 plot <- plotAbundance(
     tse, assay.type = "relabundance",
     group = "Phylum", col.var = "SampleType", add.legend = FALSE,
-    add.x.text = TRUE, facet.cols = TRUE, scales = "free_x") +
+    add.x.text = TRUE) +
     theme(axis.text.x = element_text(angle = 90))
 plot
 
diff --git a/tests/testthat/test-2plotAbundance.R b/tests/testthat/test-2plotAbundance.R
index c84a1943..8e7e2b20 100644
--- a/tests/testthat/test-2plotAbundance.R
+++ b/tests/testthat/test-2plotAbundance.R
@@ -38,7 +38,7 @@ test_that("plot abundance", {
     expect_true(all(c("colour_by","X","Y") %in% colnames(plot$data)))
     plot <- plotAbundance(
         x, assay.type = "counts", group = "Phylum", col.var = "SampleType",
-        order.col.by = "SampleType")
+        order.col.by = "SampleType", facet.cols = FALSE)
     expect_true(is.list(plot))
     expect_s3_class(plot[[1]],"ggplot")
     # Check that the grouping is correct
@@ -47,7 +47,7 @@ test_that("plot abundance", {
     rowData(x)$Salame <- sample(letters[1:5], nrow(x), replace=TRUE)
     plot <- plotAbundance(
         x, assay.type="counts", group = "Salame", col.var = "SampleType",
-        order.col.by = "SampleType")
+        order.col.by = "SampleType", facet.cols = FALSE)
     expect_true(is.list(plot))
     expect_s3_class(plot[[1]],"ggplot")
     # Expect error since too many rows
diff --git a/vignettes/miaViz.Rmd b/vignettes/miaViz.Rmd
index aa5903d8..4fbbf407 100644
--- a/vignettes/miaViz.Rmd
+++ b/vignettes/miaViz.Rmd
@@ -92,18 +92,15 @@ plotAbundance(
 ```
 
 The `features` argument is reused for plotting data along the different samples.
-In the next example the ~SampleType~ is plotted along the samples. In this case 
-the result is a list, which can combined using external tools, for example
-`patchwork`. 
+In the next example the ~SampleType~ is plotted along the samples. 
 
 ```{r plotabundance_sampletype}
-library(patchwork)
-plots <- plotAbundance(
+plotAbundance(
     GlobalPatterns[rowData(GlobalPatterns)$Phylum %in% prev_phylum],
     features = "SampleType",
     rank = "Phylum",
-    assay.type = "relabundance")
-plots$abundance / plots$SampleType + plot_layout(heights = c(9, 1))
+    assay.type = "relabundance"
+)
 ```
 
 Further example about composition barplot can be found at Orchestrating