diff --git a/DESCRIPTION b/DESCRIPTION
index 298a9da0..cb37345c 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -142,4 +142,4 @@ Collate:
     clusterdist-functions.R
     clusterdist-framework.R
     qsep.R
-RoxygenNote: 6.1.1
+RoxygenNote: 7.3.1
diff --git a/man/MCMCParams.Rd b/man/MCMCParams.Rd
index 93e81be6..39ac9ea6 100644
--- a/man/MCMCParams.Rd
+++ b/man/MCMCParams.Rd
@@ -43,17 +43,13 @@ chains(object)
 
 \S4method{length}{MCMCParams}(x)
 
-\S4method{[[}{MCMCChains,ANY,ANY}(x, i, j = "missing",
-  drop = "missing")
+\S4method{[[}{MCMCChains,ANY,ANY}(x, i, j = "missing", drop = "missing")
 
-\S4method{[[}{MCMCParams,ANY,ANY}(x, i, j = "missing",
-  drop = "missing")
+\S4method{[[}{MCMCParams,ANY,ANY}(x, i, j = "missing", drop = "missing")
 
-\S4method{[}{MCMCChains,ANY,ANY,ANY}(x, i, j = "missing",
-  drop = "missing")
+\S4method{[}{MCMCChains,ANY,ANY,ANY}(x, i, j = "missing", drop = "missing")
 
-\S4method{[}{MCMCParams,ANY,ANY,ANY}(x, i, j = "missing",
-  drop = "missing")
+\S4method{[}{MCMCParams,ANY,ANY,ANY}(x, i, j = "missing", drop = "missing")
 
 \S4method{show}{MCMCChains}(object)
 }
diff --git a/man/addGoAnnotations.Rd b/man/addGoAnnotations.Rd
index 1cf9cccc..758a4cee 100644
--- a/man/addGoAnnotations.Rd
+++ b/man/addGoAnnotations.Rd
@@ -4,8 +4,14 @@
 \alias{addGoAnnotations}
 \title{Add GO annotations}
 \usage{
-addGoAnnotations(object, params, evidence, useID = FALSE,
-  fcol = "GOAnnotations", ...)
+addGoAnnotations(
+  object,
+  params,
+  evidence,
+  useID = FALSE,
+  fcol = "GOAnnotations",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/addLegend.Rd b/man/addLegend.Rd
index 5acef64d..9fe30c89 100644
--- a/man/addLegend.Rd
+++ b/man/addLegend.Rd
@@ -4,9 +4,15 @@
 \alias{addLegend}
 \title{Adds a legend}
 \usage{
-addLegend(object, fcol = "markers", where = c("bottomleft", "bottom",
-  "bottomright", "left", "topleft", "top", "topright", "right", "center",
-  "other"), col, bty = "n", ...)
+addLegend(
+  object,
+  fcol = "markers",
+  where = c("bottomleft", "bottom", "bottomright", "left", "topleft", "top", "topright",
+    "right", "center", "other"),
+  col,
+  bty = "n",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}}
diff --git a/man/checkFeatureNamesOverlap.Rd b/man/checkFeatureNamesOverlap.Rd
index dfb1437e..f143d595 100644
--- a/man/checkFeatureNamesOverlap.Rd
+++ b/man/checkFeatureNamesOverlap.Rd
@@ -4,8 +4,7 @@
 \alias{checkFeatureNamesOverlap}
 \title{Check feature names overlap}
 \usage{
-checkFeatureNamesOverlap(x, y, fcolx = "markers", fcoly,
-  verbose = TRUE)
+checkFeatureNamesOverlap(x, y, fcolx = "markers", fcoly, verbose = TRUE)
 }
 \arguments{
 \item{x}{An \code{MSnSet} instance.}
diff --git a/man/clustDist.Rd b/man/clustDist.Rd
index 84ce57b0..fc4df2c5 100644
--- a/man/clustDist.Rd
+++ b/man/clustDist.Rd
@@ -4,8 +4,7 @@
 \alias{clustDist}
 \title{Pairwise Distance Computation for Protein Information Sets}
 \usage{
-clustDist(object, k = 1:5, fcol = "GOAnnotations", n = 5,
-  verbose = TRUE, seed)
+clustDist(object, k = 1:5, fcol = "GOAnnotations", n = 5, verbose = TRUE, seed)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
@@ -48,7 +47,7 @@ the \code{kmeans} algorithm fits and tests \code{k = c(1:5)}
 the mean pairwise distance for each \code{k} tested.
 
 Note: currently distances are calcualted in Euclidean space, 
-but other distance metrics will be supported in the future).
+but other distance metrics will be supported in the future). 
 
 The output is a \code{list} of \code{ClustDist} objects, 
 one per information cluster. The \code{ClustDist} 
diff --git a/man/fDataToUnknown.Rd b/man/fDataToUnknown.Rd
index 9d0bd026..49b7aa0f 100644
--- a/man/fDataToUnknown.Rd
+++ b/man/fDataToUnknown.Rd
@@ -4,8 +4,7 @@
 \alias{fDataToUnknown}
 \title{Update a feature variable}
 \usage{
-fDataToUnknown(object, fcol = "markers", from = "^$", to = "unknown",
-  ...)
+fDataToUnknown(object, fcol = "markers", from = "^$", to = "unknown", ...)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/filterMaxMarkers.Rd b/man/filterMaxMarkers.Rd
index 9389de4f..c63b42eb 100644
--- a/man/filterMaxMarkers.Rd
+++ b/man/filterMaxMarkers.Rd
@@ -5,8 +5,7 @@
 \title{Removes class/annotation information from a matrix of candidate
 markers that appear in the \code{fData}.}
 \usage{
-filterMaxMarkers(object, n, p = 0.2, fcol = "GOAnnotations",
-  verbose = TRUE)
+filterMaxMarkers(object, n, p = 0.2, fcol = "GOAnnotations", verbose = TRUE)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/filterMinMarkers.Rd b/man/filterMinMarkers.Rd
index 853aa515..3bb704e3 100644
--- a/man/filterMinMarkers.Rd
+++ b/man/filterMinMarkers.Rd
@@ -5,8 +5,7 @@
 \title{Removes class/annotation information from a matrix of candidate
 markers that appear in the \code{fData}.}
 \usage{
-filterMinMarkers(object, n = 10, p, fcol = "GOAnnotations",
-  verbose = TRUE)
+filterMinMarkers(object, n = 10, p, fcol = "GOAnnotations", verbose = TRUE)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/getGOFromFeatures.Rd b/man/getGOFromFeatures.Rd
index c128b51b..5d7263b4 100644
--- a/man/getGOFromFeatures.Rd
+++ b/man/getGOFromFeatures.Rd
@@ -4,8 +4,14 @@
 \alias{getGOFromFeatures}
 \title{Retrieve GO terms for feature names}
 \usage{
-getGOFromFeatures(id, namespace = "cellular_component",
-  evidence = NULL, params = NULL, verbose = FALSE, nmax = 500)
+getGOFromFeatures(
+  id,
+  namespace = "cellular_component",
+  evidence = NULL,
+  params = NULL,
+  verbose = FALSE,
+  nmax = 500
+)
 }
 \arguments{
 \item{id}{An \code{character} with feature names to be pulled from
diff --git a/man/getPredictions.Rd b/man/getPredictions.Rd
index fb77faf0..7606ba5c 100644
--- a/man/getPredictions.Rd
+++ b/man/getPredictions.Rd
@@ -4,8 +4,7 @@
 \alias{getPredictions}
 \title{Returns the predictions in an 'MSnSet'}
 \usage{
-getPredictions(object, fcol, scol, mcol = "markers", t = 0,
-  verbose = TRUE)
+getPredictions(object, fcol, scol, mcol = "markers", t = 0, verbose = TRUE)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/highlightOnPlot.Rd b/man/highlightOnPlot.Rd
index 110b17cf..767b4192 100644
--- a/man/highlightOnPlot.Rd
+++ b/man/highlightOnPlot.Rd
@@ -7,8 +7,7 @@
 \usage{
 highlightOnPlot(object, foi, labels, args = list(), ...)
 
-highlightOnPlot3D(object, foi, labels, args = list(), radius = 0.1 * 3,
-  ...)
+highlightOnPlot3D(object, foi, labels, args = list(), radius = 0.1 * 3, ...)
 }
 \arguments{
 \item{object}{The main dataset described as an \code{MSnSet} or a
@@ -22,7 +21,7 @@ or, alternatively, a \code{character} of feautre names.}
 variable name to be used to label the features of
 interest. This is only valid if \code{object} is an
 \code{MSnSet}. Alternatively, if \code{TRUE}, then
-\code{featureNames(object)} (or code{rownames(object)}, if
+\code{featureNames(object)} (or \code{rownames(object)}, if
 \code{object} is a \code{matrix}) are used. Default is
 missing, which does not add any label.s}
 
@@ -48,7 +47,7 @@ NULL; used for its side effects.
 \description{
 Highlights a set of features of interest given as a
 \code{FeaturesOfInterest} instance on a PCA plot produced by
-code{plot2D} or \code{plot3D}. If none of the features of interest
+\code{plot2D} or \code{plot3D}. If none of the features of interest
 are found in the \code{MSnset}'s \code{featureNames}, an warning
 is thrown.
 }
diff --git a/man/knnClassification.Rd b/man/knnClassification.Rd
index d30a8f92..1d767a65 100644
--- a/man/knnClassification.Rd
+++ b/man/knnClassification.Rd
@@ -5,8 +5,14 @@
 \alias{knnPrediction}
 \title{knn classification}
 \usage{
-knnClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), k, fcol = "markers", ...)
+knnClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  k,
+  fcol = "markers",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/knnOptimisation.Rd b/man/knnOptimisation.Rd
index 53513d73..a4d6ed81 100644
--- a/man/knnOptimisation.Rd
+++ b/man/knnOptimisation.Rd
@@ -6,9 +6,18 @@
 \alias{knnRegularisation}
 \title{knn parameter optimisation}
 \usage{
-knnOptimisation(object, fcol = "markers", k = seq(3, 15, 2),
-  times = 100, test.size = 0.2, xval = 5, fun = mean, seed,
-  verbose = TRUE, ...)
+knnOptimisation(
+  object,
+  fcol = "markers",
+  k = seq(3, 15, 2),
+  times = 100,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/knntlClassification.Rd b/man/knntlClassification.Rd
index b4055f75..7fb84097 100644
--- a/man/knntlClassification.Rd
+++ b/man/knntlClassification.Rd
@@ -4,8 +4,15 @@
 \alias{knntlClassification}
 \title{knn transfer learning classification}
 \usage{
-knntlClassification(primary, auxiliary, fcol = "markers", bestTheta, k,
-  scores = c("prediction", "all", "none"), seed)
+knntlClassification(
+  primary,
+  auxiliary,
+  fcol = "markers",
+  bestTheta,
+  k,
+  scores = c("prediction", "all", "none"),
+  seed
+)
 }
 \arguments{
 \item{primary}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/knntlOptimisation.Rd b/man/knntlOptimisation.Rd
index ad4c7678..6544e27f 100644
--- a/man/knntlOptimisation.Rd
+++ b/man/knntlOptimisation.Rd
@@ -4,10 +4,23 @@
 \alias{knntlOptimisation}
 \title{theta parameter optimisation}
 \usage{
-knntlOptimisation(primary, auxiliary, fcol = "markers", k, times = 50,
-  test.size = 0.2, xval = 5, by = 0.5, length.out, th, xfolds,
-  BPPARAM = BiocParallel::bpparam(), method = "Breckels",
-  log = FALSE, seed)
+knntlOptimisation(
+  primary,
+  auxiliary,
+  fcol = "markers",
+  k,
+  times = 50,
+  test.size = 0.2,
+  xval = 5,
+  by = 0.5,
+  length.out,
+  th,
+  xfolds,
+  BPPARAM = BiocParallel::bpparam(),
+  method = "Breckels",
+  log = FALSE,
+  seed
+)
 }
 \arguments{
 \item{primary}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/ksvmClassification.Rd b/man/ksvmClassification.Rd
index b53bdbdb..9f706315 100644
--- a/man/ksvmClassification.Rd
+++ b/man/ksvmClassification.Rd
@@ -5,8 +5,14 @@
 \alias{ksvmPrediction}
 \title{ksvm classification}
 \usage{
-ksvmClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), cost, fcol = "markers", ...)
+ksvmClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  cost,
+  fcol = "markers",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/ksvmOptimisation.Rd b/man/ksvmOptimisation.Rd
index fe011412..2dad3d16 100644
--- a/man/ksvmOptimisation.Rd
+++ b/man/ksvmOptimisation.Rd
@@ -6,9 +6,18 @@
 \alias{ksvmOptimization}
 \title{ksvm parameter optimisation}
 \usage{
-ksvmOptimisation(object, fcol = "markers", cost = 2^(-4:4),
-  times = 100, test.size = 0.2, xval = 5, fun = mean, seed,
-  verbose = TRUE, ...)
+ksvmOptimisation(
+  object,
+  fcol = "markers",
+  cost = 2^(-4:4),
+  times = 100,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/makeGoSet.Rd b/man/makeGoSet.Rd
index 03b11aa9..8a808ca7 100644
--- a/man/makeGoSet.Rd
+++ b/man/makeGoSet.Rd
@@ -4,8 +4,7 @@
 \alias{makeGoSet}
 \title{Creates a GO feature \code{MSnSet}}
 \usage{
-makeGoSet(object, params, namespace = "cellular_component",
-  evidence = NULL)
+makeGoSet(object, params, namespace = "cellular_component", evidence = NULL)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}
diff --git a/man/mcmc-helpers.Rd b/man/mcmc-helpers.Rd
index 7fa32f19..1ec6c82f 100644
--- a/man/mcmc-helpers.Rd
+++ b/man/mcmc-helpers.Rd
@@ -1,6 +1,5 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/machinelearning-functions-tagm-mcmc-helper.R
-\docType{methods}
 \name{mcmc_get_outliers}
 \alias{mcmc_get_outliers}
 \alias{mcmc_get_meanComponent}
diff --git a/man/mrkHClust.Rd b/man/mrkHClust.Rd
index 8c6150d5..d0da4584 100644
--- a/man/mrkHClust.Rd
+++ b/man/mrkHClust.Rd
@@ -4,8 +4,15 @@
 \alias{mrkHClust}
 \title{Draw a dendrogram of subcellular clusters}
 \usage{
-mrkHClust(object, fcol = "markers", distargs, hclustargs,
-  method = mean, plot = TRUE, ...)
+mrkHClust(
+  object,
+  fcol = "markers",
+  distargs,
+  hclustargs,
+  method = mean,
+  plot = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/nbClassification.Rd b/man/nbClassification.Rd
index bf744a36..7690736f 100644
--- a/man/nbClassification.Rd
+++ b/man/nbClassification.Rd
@@ -5,8 +5,14 @@
 \alias{nbPrediction}
 \title{nb classification}
 \usage{
-nbClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), laplace, fcol = "markers", ...)
+nbClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  laplace,
+  fcol = "markers",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/nbOptimisation.Rd b/man/nbOptimisation.Rd
index 889e0c21..7088c504 100644
--- a/man/nbOptimisation.Rd
+++ b/man/nbOptimisation.Rd
@@ -6,9 +6,18 @@
 \alias{nbOptimization}
 \title{nb paramter optimisation}
 \usage{
-nbOptimisation(object, fcol = "markers", laplace = seq(0, 5, 0.5),
-  times = 100, test.size = 0.2, xval = 5, fun = mean, seed,
-  verbose = TRUE, ...)
+nbOptimisation(
+  object,
+  fcol = "markers",
+  laplace = seq(0, 5, 0.5),
+  times = 100,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/nicheMeans2D.Rd b/man/nicheMeans2D.Rd
index 09b34931..06eca089 100644
--- a/man/nicheMeans2D.Rd
+++ b/man/nicheMeans2D.Rd
@@ -4,8 +4,14 @@
 \alias{nicheMeans2D}
 \title{Uncertainty plot organelle means}
 \usage{
-nicheMeans2D(object, params, priors, dims = c(1, 2), fcol = "markers",
-  aspect = 0.5)
+nicheMeans2D(
+  object,
+  params,
+  priors,
+  dims = c(1, 2),
+  fcol = "markers",
+  aspect = 0.5
+)
 }
 \arguments{
 \item{object}{A valid object of class \code{MSnset}}
diff --git a/man/nnetClassification.Rd b/man/nnetClassification.Rd
index 9ee8b4d0..b0f1b28e 100644
--- a/man/nnetClassification.Rd
+++ b/man/nnetClassification.Rd
@@ -5,8 +5,15 @@
 \alias{nnetPrediction}
 \title{nnet classification}
 \usage{
-nnetClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), decay, size, fcol = "markers", ...)
+nnetClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  decay,
+  size,
+  fcol = "markers",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/nnetOptimisation.Rd b/man/nnetOptimisation.Rd
index f1cd4856..57401386 100644
--- a/man/nnetOptimisation.Rd
+++ b/man/nnetOptimisation.Rd
@@ -6,9 +6,19 @@
 \alias{nnetOptimization}
 \title{nnet parameter optimisation}
 \usage{
-nnetOptimisation(object, fcol = "markers", decay = c(0, 10^(-1:-5)),
-  size = seq(1, 10, 2), times = 100, test.size = 0.2, xval = 5,
-  fun = mean, seed, verbose = TRUE, ...)
+nnetOptimisation(
+  object,
+  fcol = "markers",
+  decay = c(0, 10^(-1:-5)),
+  size = seq(1, 10, 2),
+  times = 100,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/orderGoAnnotations.Rd b/man/orderGoAnnotations.Rd
index b4940edf..45d75c6a 100644
--- a/man/orderGoAnnotations.Rd
+++ b/man/orderGoAnnotations.Rd
@@ -4,8 +4,15 @@
 \alias{orderGoAnnotations}
 \title{Orders annotation information}
 \usage{
-orderGoAnnotations(object, fcol = "GOAnnotations", k = 1:5, n = 5,
-  p = 1/3, verbose = TRUE, seed)
+orderGoAnnotations(
+  object,
+  fcol = "GOAnnotations",
+  k = 1:5,
+  n = 5,
+  p = 1/3,
+  verbose = TRUE,
+  seed
+)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
@@ -37,7 +44,7 @@ the best fit with the data.
 As there are typically many protein/annotation sets that may fit the data
 we order protein sets by best fit i.e. cluster tightness, by
 computing the mean normalised Euclidean distance for all instances 
-per protein set.
+per protein set. 
 
 For each protein set i.e. proteins that have been labelled
 with a specified term/information criteria, we find the best 
@@ -46,13 +53,13 @@ test\code{k = 1:5}) according to the minimum mean normalised
 pairwise Euclidean distance over all component clusters. 
 (Note: when testing \code{k} if any components are found to 
 have less than \code{n} proteins these components are not
-included and \code{k} is reduced by 1).
+included and \code{k} is reduced by 1). 
 
 Each component cluster is normalised by \code{N^p} (where 
 \code{N} is the total number of proteins per component, 
 and \code{p} is the power). Hueristally, \code{p = 1/3} 
 and normalising by \code{N^1/3} has been found the optimum 
-normalisation factor.
+normalisation factor. 
 
 Candidates in the matrix are ordered according to lowest 
 mean normalised pairwise Euclidean distance as we expect 
diff --git a/man/perTurboClassification.Rd b/man/perTurboClassification.Rd
index c5c56828..a68a354c 100644
--- a/man/perTurboClassification.Rd
+++ b/man/perTurboClassification.Rd
@@ -4,8 +4,16 @@
 \alias{perTurboClassification}
 \title{perTurbo classification}
 \usage{
-perTurboClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), pRegul, sigma, inv, reg, fcol = "markers")
+perTurboClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  pRegul,
+  sigma,
+  inv,
+  reg,
+  fcol = "markers"
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/perTurboOptimisation.Rd b/man/perTurboOptimisation.Rd
index 450908f1..a84eb6bb 100644
--- a/man/perTurboOptimisation.Rd
+++ b/man/perTurboOptimisation.Rd
@@ -5,11 +5,20 @@
 \alias{perTurboOptimization}
 \title{PerTurbo parameter optimisation}
 \usage{
-perTurboOptimisation(object, fcol = "markers", pRegul = 10^(seq(from =
-  -1, to = 0, by = 0.2)), sigma = 10^(seq(from = -1, to = 1, by = 0.5)),
+perTurboOptimisation(
+  object,
+  fcol = "markers",
+  pRegul = 10^(seq(from = -1, to = 0, by = 0.2)),
+  sigma = 10^(seq(from = -1, to = 1, by = 0.5)),
   inv = c("Inversion Cholesky", "Moore Penrose", "solve", "svd"),
-  reg = c("tikhonov", "none", "trunc"), times = 1, test.size = 0.2,
-  xval = 5, fun = mean, seed, verbose = TRUE)
+  reg = c("tikhonov", "none", "trunc"),
+  times = 1,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/phenoDisco.Rd b/man/phenoDisco.Rd
index 97d1fb6a..11073feb 100644
--- a/man/phenoDisco.Rd
+++ b/man/phenoDisco.Rd
@@ -4,10 +4,23 @@
 \alias{phenoDisco}
 \title{Runs the \code{phenoDisco} algorithm.}
 \usage{
-phenoDisco(object, fcol = "markers", times = 100, GS = 10,
-  allIter = FALSE, p = 0.05, ndims = 2,
-  modelNames = mclust.options("emModelNames"), G = 1:9, BPPARAM,
-  tmpfile, seed, verbose = TRUE, dimred = c("PCA", "t-SNE"), ...)
+phenoDisco(
+  object,
+  fcol = "markers",
+  times = 100,
+  GS = 10,
+  allIter = FALSE,
+  p = 0.05,
+  ndims = 2,
+  modelNames = mclust.options("emModelNames"),
+  G = 1:9,
+  BPPARAM,
+  tmpfile,
+  seed,
+  verbose = TRUE,
+  dimred = c("PCA", "t-SNE"),
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/plot2D.Rd b/man/plot2D.Rd
index 3c5b1e27..911850ae 100644
--- a/man/plot2D.Rd
+++ b/man/plot2D.Rd
@@ -1,20 +1,44 @@
 % Generated by roxygen2: do not edit by hand
 % Please edit documentation in R/plotting.R, R/plotting3.R
-\docType{methods}
 \name{plot2D}
 \alias{plot2D}
 \alias{plot2Dmethods}
 \alias{plot3D,MSnSet-method}
 \title{Plot organelle assignment data and results.}
 \usage{
-plot2D(object, fcol = "markers", fpch, unknown = "unknown",
-  dims = 1:2, score = 1, method = "PCA", methargs,
-  axsSwitch = FALSE, mirrorX = FALSE, mirrorY = FALSE, col, pch, cex,
-  index = FALSE, idx.cex = 0.75, addLegend, identify = FALSE,
-  plot = TRUE, grid = TRUE, ...)
-
-\S4method{plot3D}{MSnSet}(object, fcol = "markers", dims = c(1, 2, 3),
-  radius1 = 0.1, radius2 = radius1 * 2, plot = TRUE, ...)
+plot2D(
+  object,
+  fcol = "markers",
+  fpch,
+  unknown = "unknown",
+  dims = 1:2,
+  score = 1,
+  method = "PCA",
+  methargs,
+  axsSwitch = FALSE,
+  mirrorX = FALSE,
+  mirrorY = FALSE,
+  col,
+  pch,
+  cex,
+  index = FALSE,
+  idx.cex = 0.75,
+  addLegend,
+  identify = FALSE,
+  plot = TRUE,
+  grid = TRUE,
+  ...
+)
+
+\S4method{plot3D}{MSnSet}(
+  object,
+  fcol = "markers",
+  dims = c(1, 2, 3),
+  radius1 = 0.1,
+  radius2 = radius1 * 2,
+  plot = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/plot2Ds.Rd b/man/plot2Ds.Rd
index dcdd64e9..2d66197f 100644
--- a/man/plot2Ds.Rd
+++ b/man/plot2Ds.Rd
@@ -8,9 +8,20 @@
 \alias{col2}
 \title{Draw 2 data sets on one PCA plot}
 \usage{
-plot2Ds(object, pcol, fcol = "markers", cex.x = 1, cex.y = 1,
-  pch.x = 21, pch.y = 23, col, mirrorX = FALSE, mirrorY = FALSE,
-  plot = TRUE, ...)
+plot2Ds(
+  object,
+  pcol,
+  fcol = "markers",
+  cex.x = 1,
+  cex.y = 1,
+  pch.x = 21,
+  pch.y = 23,
+  col,
+  mirrorX = FALSE,
+  mirrorY = FALSE,
+  plot = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An \code{\linkS4class{MSnSet}} or a
diff --git a/man/plotDist.Rd b/man/plotDist.Rd
index bc77c92c..c91cde7f 100644
--- a/man/plotDist.Rd
+++ b/man/plotDist.Rd
@@ -4,10 +4,21 @@
 \alias{plotDist}
 \title{Plots the distribution of features across fractions}
 \usage{
-plotDist(object, markers, fcol = NULL, mcol = "steelblue",
-  pcol = getUnknowncol(), alpha = 0.3, type = "b", lty = 1,
-  fractions = sampleNames(object), ylab = "Intensity",
-  xlab = "Fractions", ylim, ...)
+plotDist(
+  object,
+  markers,
+  fcol = NULL,
+  mcol = "steelblue",
+  pcol = getUnknowncol(),
+  alpha = 0.3,
+  type = "b",
+  lty = 1,
+  fractions = sampleNames(object),
+  ylab = "Intensity",
+  xlab = "Fractions",
+  ylim,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet}.}
diff --git a/man/plsdaClassification.Rd b/man/plsdaClassification.Rd
index 1722f013..93381b0d 100644
--- a/man/plsdaClassification.Rd
+++ b/man/plsdaClassification.Rd
@@ -5,8 +5,14 @@
 \alias{plsdaPrediction}
 \title{plsda classification}
 \usage{
-plsdaClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), ncomp, fcol = "markers", ...)
+plsdaClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  ncomp,
+  fcol = "markers",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/plsdaOptimisation.Rd b/man/plsdaOptimisation.Rd
index 70ef1ef6..05486d4b 100644
--- a/man/plsdaOptimisation.Rd
+++ b/man/plsdaOptimisation.Rd
@@ -6,8 +6,18 @@
 \alias{plsdaOptimization}
 \title{plsda parameter optimisation}
 \usage{
-plsdaOptimisation(object, fcol = "markers", ncomp = 2:6, times = 100,
-  test.size = 0.2, xval = 5, fun = mean, seed, verbose = TRUE, ...)
+plsdaOptimisation(
+  object,
+  fcol = "markers",
+  ncomp = 2:6,
+  times = 100,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/rfClassification.Rd b/man/rfClassification.Rd
index e4950801..60a7f550 100644
--- a/man/rfClassification.Rd
+++ b/man/rfClassification.Rd
@@ -5,8 +5,14 @@
 \alias{rfPrediction}
 \title{rf classification}
 \usage{
-rfClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), mtry, fcol = "markers", ...)
+rfClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  mtry,
+  fcol = "markers",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/rfOptimisation.Rd b/man/rfOptimisation.Rd
index c6792938..ed1cf7a0 100644
--- a/man/rfOptimisation.Rd
+++ b/man/rfOptimisation.Rd
@@ -6,8 +6,18 @@
 \alias{rfOptimization}
 \title{svm parameter optimisation}
 \usage{
-rfOptimisation(object, fcol = "markers", mtry = NULL, times = 100,
-  test.size = 0.2, xval = 5, fun = mean, seed, verbose = TRUE, ...)
+rfOptimisation(
+  object,
+  fcol = "markers",
+  mtry = NULL,
+  times = 100,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/spatial2D.Rd b/man/spatial2D.Rd
index 7e274268..a1c47d7a 100644
--- a/man/spatial2D.Rd
+++ b/man/spatial2D.Rd
@@ -4,9 +4,16 @@
 \alias{spatial2D}
 \title{Uncertainty plot in localisation probabilities}
 \usage{
-spatial2D(object, dims = c(1, 2), cov.function = fields::wendland.cov,
-  theta = 1, derivative = 2, k = 1, breaks = c(0.99, 0.95, 0.9,
-  0.85, 0.8, 0.75, 0.7), aspect = 0.5)
+spatial2D(
+  object,
+  dims = c(1, 2),
+  cov.function = fields::wendland.cov,
+  theta = 1,
+  derivative = 2,
+  k = 1,
+  breaks = c(0.99, 0.95, 0.9, 0.85, 0.8, 0.75, 0.7),
+  aspect = 0.5
+)
 }
 \arguments{
 \item{object}{A valid object of class \code{MSnset} with mcmc prediction
diff --git a/man/svmClassification.Rd b/man/svmClassification.Rd
index 4d3717d8..2a4458fb 100644
--- a/man/svmClassification.Rd
+++ b/man/svmClassification.Rd
@@ -5,8 +5,15 @@
 \alias{svmPrediction}
 \title{svm classification}
 \usage{
-svmClassification(object, assessRes, scores = c("prediction", "all",
-  "none"), cost, sigma, fcol = "markers", ...)
+svmClassification(
+  object,
+  assessRes,
+  scores = c("prediction", "all", "none"),
+  cost,
+  sigma,
+  fcol = "markers",
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/svmOptimisation.Rd b/man/svmOptimisation.Rd
index 70c29ede..2ebfe07f 100644
--- a/man/svmOptimisation.Rd
+++ b/man/svmOptimisation.Rd
@@ -6,9 +6,19 @@
 \alias{svmOptimization}
 \title{svm parameter optimisation}
 \usage{
-svmOptimisation(object, fcol = "markers", cost = 2^(-4:4),
-  sigma = 10^(-3:2), times = 100, test.size = 0.2, xval = 5,
-  fun = mean, seed, verbose = TRUE, ...)
+svmOptimisation(
+  object,
+  fcol = "markers",
+  cost = 2^(-4:4),
+  sigma = 10^(-3:2),
+  times = 100,
+  test.size = 0.2,
+  xval = 5,
+  fun = mean,
+  seed,
+  verbose = TRUE,
+  ...
+)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/tagm-map.Rd b/man/tagm-map.Rd
index 8b327386..89b48224 100644
--- a/man/tagm-map.Rd
+++ b/man/tagm-map.Rd
@@ -17,15 +17,31 @@ each iteration of the EM algorithm to check for convergence.}
 
 logPosteriors(x)
 
-tagmMapTrain(object, fcol = "markers", method = "MAP", numIter = 100,
-  mu0 = NULL, lambda0 = 0.01, nu0 = NULL, S0 = NULL,
-  beta0 = NULL, u = 2, v = 10, seed = NULL)
-
-tagmMapPredict(object, params, fcol = "markers", probJoint = FALSE,
-  probOutlier = TRUE)
+tagmMapTrain(
+  object,
+  fcol = "markers",
+  method = "MAP",
+  numIter = 100,
+  mu0 = NULL,
+  lambda0 = 0.01,
+  nu0 = NULL,
+  S0 = NULL,
+  beta0 = NULL,
+  u = 2,
+  v = 10,
+  seed = NULL
+)
+
+tagmMapPredict(
+  object,
+  params,
+  fcol = "markers",
+  probJoint = FALSE,
+  probOutlier = TRUE
+)
 }
 \arguments{
-\item{object}{An \code{\link[MSnbase:MSnSet]{MSnbase::MSnSet}} containing the spatial
+\item{object}{An \code{\link[MSnbase:MSnSet-class]{MSnbase::MSnSet}} containing the spatial
 proteomics data to be passed to \code{tagmMapTrain} and
 \code{tagmPredict}.}
 
@@ -77,7 +93,7 @@ considered an outlier).}
 \code{tagmMapTrain} returns an instance of class \code{\link[=MAPParams]{MAPParams()}}.
 
 \code{tagmPredict} returns an instance of class
-\code{\link[MSnbase:MSnSet]{MSnbase::MSnSet}} containing the localisation predictions as
+\code{\link[MSnbase:MSnSet-class]{MSnbase::MSnSet}} containing the localisation predictions as
 a new \code{tagm.map.allocation} feature variable.
 }
 \description{
@@ -88,7 +104,7 @@ using the maximum a posteriori (MAP) optimisation routine.
 \details{
 The \code{tagmMapTrain} function generates the MAP parameters (object or class
 \code{MAPParams}) based on an annotated quantitative spatial proteomics dataset
-(object of class \code{\link[MSnbase:MSnSet]{MSnbase::MSnSet}}). Both are then passed to the
+(object of class \code{\link[MSnbase:MSnSet-class]{MSnbase::MSnSet}}). Both are then passed to the
 \code{tagmPredict} function to predict the sub-cellular localisation of protein
 of unknown localisation. See the \emph{pRoloc-bayesian} vignette for details and
 examples. In this implementation, if numerical instability is detected in
diff --git a/man/tagm-mcmc.Rd b/man/tagm-mcmc.Rd
index 8b5edd46..bb33fd33 100644
--- a/man/tagm-mcmc.Rd
+++ b/man/tagm-mcmc.Rd
@@ -7,21 +7,44 @@
 \alias{tagmMcmcProcess}
 \title{Localisation of proteins using the TAGM MCMC method}
 \usage{
-tagmMcmcTrain(object, fcol = "markers", method = "MCMC",
-  numIter = 1000L, burnin = 100L, thin = 5L, mu0 = NULL,
-  lambda0 = 0.01, nu0 = NULL, S0 = NULL, beta0 = NULL, u = 2,
-  v = 10, numChains = 4L, BPPARAM = BiocParallel::bpparam())
-
-tagmMcmcPredict(object, params, fcol = "markers", probJoint = FALSE,
-  probOutlier = TRUE)
-
-tagmPredict(object, params, fcol = "markers", probJoint = FALSE,
-  probOutlier = TRUE)
+tagmMcmcTrain(
+  object,
+  fcol = "markers",
+  method = "MCMC",
+  numIter = 1000L,
+  burnin = 100L,
+  thin = 5L,
+  mu0 = NULL,
+  lambda0 = 0.01,
+  nu0 = NULL,
+  S0 = NULL,
+  beta0 = NULL,
+  u = 2,
+  v = 10,
+  numChains = 4L,
+  BPPARAM = BiocParallel::bpparam()
+)
+
+tagmMcmcPredict(
+  object,
+  params,
+  fcol = "markers",
+  probJoint = FALSE,
+  probOutlier = TRUE
+)
+
+tagmPredict(
+  object,
+  params,
+  fcol = "markers",
+  probJoint = FALSE,
+  probOutlier = TRUE
+)
 
 tagmMcmcProcess(params)
 }
 \arguments{
-\item{object}{An \code{\link[MSnbase:MSnSet]{MSnbase::MSnSet}} containing the spatial
+\item{object}{An \code{\link[MSnbase:MSnSet-class]{MSnbase::MSnSet}} containing the spatial
 proteomics data to be passed to \code{tagmMcmcTrain} and
 \code{tagmPredict}.}
 
@@ -87,7 +110,7 @@ considered an outlier).}
 \code{MCMCParams}.
 
 \code{tagmMcmcPredict} returns an instance of class
-\code{\link[MSnbase:MSnSet]{MSnbase::MSnSet}} containing the localisation predictions as
+\code{\link[MSnbase:MSnSet-class]{MSnbase::MSnSet}} containing the localisation predictions as
 a new \code{tagm.mcmc.allocation} feature variable. The allocation
 probability is encoded as \code{tagm.mcmc.probability}
 (corresponding to the mean of the distribution
@@ -112,7 +135,7 @@ using Markov-chain Monte-Carlo (MCMC) for inference.
 The \code{tagmMcmcTrain} function generates the samples from the
 posterior distributions (object or class \code{MCMCParams}) based on an
 annotated quantitative spatial proteomics dataset (object of class
-\code{\link[MSnbase:MSnSet]{MSnbase::MSnSet}}). Both are then passed to the \code{tagmPredict}
+\code{\link[MSnbase:MSnSet-class]{MSnbase::MSnSet}}). Both are then passed to the \code{tagmPredict}
 function to predict the sub-cellular localisation of protein of
 unknown localisation. See the \emph{pRoloc-bayesian} vignette for
 details and examples. In this implementation, if numerical instability
diff --git a/man/testMarkers.Rd b/man/testMarkers.Rd
index 79276e8d..1f0230a2 100644
--- a/man/testMarkers.Rd
+++ b/man/testMarkers.Rd
@@ -4,8 +4,7 @@
 \alias{testMarkers}
 \title{Tests marker class sizes}
 \usage{
-testMarkers(object, xval = 5, n = 2, fcol = "markers",
-  error = FALSE)
+testMarkers(object, xval = 5, n = 2, fcol = "markers", error = FALSE)
 }
 \arguments{
 \item{object}{An instance of class \code{"\linkS4class{MSnSet}"}.}
diff --git a/man/zerosInBinMSnSet.Rd b/man/zerosInBinMSnSet.Rd
index d3b09e44..6cb0c120 100644
--- a/man/zerosInBinMSnSet.Rd
+++ b/man/zerosInBinMSnSet.Rd
@@ -4,8 +4,7 @@
 \alias{zerosInBinMSnSet}
 \title{Compute the number of non-zero values in each marker classes}
 \usage{
-zerosInBinMSnSet(object, fcol = "markers", as.matrix = TRUE,
-  percent = TRUE)
+zerosInBinMSnSet(object, fcol = "markers", as.matrix = TRUE, percent = TRUE)
 }
 \arguments{
 \item{object}{An instance of class \code{MSnSet} with binary data.}
diff --git a/src/RcppExports.cpp b/src/RcppExports.cpp
index 4372b7da..8b7986dc 100644
--- a/src/RcppExports.cpp
+++ b/src/RcppExports.cpp
@@ -6,6 +6,11 @@
 
 using namespace Rcpp;
 
+#ifdef RCPP_USE_GLOBAL_ROSTREAM
+Rcpp::Rostream<true>&  Rcpp::Rcout = Rcpp::Rcpp_cout_get();
+Rcpp::Rostream<false>& Rcpp::Rcerr = Rcpp::Rcpp_cerr_get();
+#endif
+
 // dmvtCpp
 SEXP dmvtCpp(arma::mat X_, arma::vec mu_, arma::mat sigma_, double df_, bool log_, unsigned int ncores_, bool isChol_);
 RcppExport SEXP _pRoloc_dmvtCpp(SEXP X_SEXP, SEXP mu_SEXP, SEXP sigma_SEXP, SEXP df_SEXP, SEXP log_SEXP, SEXP ncores_SEXP, SEXP isChol_SEXP) {