This vignette describes the implemented functionality in the
pRolocGUI package. The package is based on the
(Gatto and Lilley, 2012)
and on the functions defined in the package
(Breckels, Gatto, Christoforou, Groen, et al., 2013; Gatto, Breckels, Wieczorek, Burger, et al., 2014).
pRolocGUI is intended for the visualisation and analysis of proteomics data,
especially for the analyses of
(Dunkley, Hester, Shadforth, Runions, et al., 2006)
(Foster, Hoog, Zhang, Zhang, et al., 2006) experiments.
To achieve reactivity and interactivity,
pRolocGUI relies on the
The implemented application facilitates a higher degree of interactivity
with the underlying spatial proteomics data: The distributed functions
pRolocComp offer interactive
Principal Component Analysis (PCA) plots and
protein profile plots, as well as exploration of quantitative and
Key features of
pRolocComp are the identification of
features in plots, a 'reverse search' based on querying meta-data which
allows for highlighting the features on plots and an import/export
functionality by using the
distributed by the
MSnbase package. Additionally,
pRolocComp allows for
comparison of two comparable
MSnSet instances, e.g. this might be of great
help for analyses of changes in protein localisation in different
We recommend some familiarity with the
MSnSet class (see
for details) and the
pRoloc vignette (available with
pRolocGUI is under active development; current functionality is
evolving and new features will be added. This software is free and
open-source. You are invited to contact Laurent Gatto (email@example.com) or
Thomas Naake (firstname.lastname@example.org) in case you have any questions,
suggestions or have found any bugs or typos. To reach a broader audience for
more general questions about proteomics analyses using R consider of writing
to the Bioconductor list.
pRolocGUI distributes the
pRolocVis needs an object of class
a list of
MSnSet objects as an argument, while
pRolocComp needs a list
containing two instances of class
To prepare the environment to run a
pRolocGUI package and for demonstration purposes four example
are loaded to the environment. The example data sets are available from the
(Gatto and Breckels, 2014) experiment
package and are derived from experiments
Breckels, Gatto, Christoforou, Groen, et al. (2013),
the first and second replicate from
Tan, Dvinge, Christoforou, Bertone, et al. (2009)
Dunkley, Hester, Shadforth, Runions, et al. (2006).
library("pRolocGUI") data(andy2011, package = "pRolocdata") data(tan2009r1, package = "pRolocdata") data(tan2009r2, package = "pRolocdata") data(dunkley2006, package = "pRolocdata")
pRolocVis needs an object of class
MSnSet as an argument. We can launch the
application with an
MSnSet by assigning it to the argument
pRolocVis(object = andy2011)
Alternatively, to upload multiple objects of class
accepts both lists with named and unnamed objects. This allows for analysis
of multiple data sets without stopping the application from running.
The names of objects of lists will appear in the drop-down menu in the
data tab, while lists with unnamed objects will have a drop-down menu
with automatically named entries as a consequence, i.e. object 1 ... object n,
where n is the length of the list.
namedVis <- list(andy2011 = andy2011, tan2009r1 = tan2009r1, dunkley2006 = dunkley2006) unnamedVis <- list(andy2011, tan2009r1, dunkley2006) pRolocVis(object = namedVis) pRolocVis(object = unnamedVis)
pRolocComp requires a list of two
MSnSets which can be named or unnamed.
namedComp <- list(tan2009r1 = tan2009r1, tan2009r2 = tan2009r2) unnamedComp <- list(tan2009r1, tan2009r2) pRolocComp(object = namedComp) pRolocComp(object = unnamedComp)
N.B.! It is also possible to use a partly named list in
pRolocComp will open a new tab in your default
To stop the applications from running press
Ctrl-C in the
console (or use the "STOP" button when using RStudio) and close the
browser tab, where
pRolocComp is running.
To optimise ease of use the interfaces of
subdivided in seven tabs:
You browse through the tabs by simply clicking on them. Each tab selected will have a different kind of appearance while some (PCA, protein profiles, quantitation and feature meta-data) share a common feature in the sidebar, the Display selection widget (see section 3. Display selection widget for further details).
In case you have a question and want to consult the vignette for a certain
issue (e.g. regarding PCA tab or on how to use the Display selection
widget) click on
? which will open the vignette in a new browser tab in the
In general, the tabs for
pRolocComp will look alike. The tab
data however differs for the two applications. While in
tab allows for the selection of the used
MSnSet and the upload of
.Rdata files, in
pRolocComp there is the possibility to subset the used
MSnSets (in terms of using common, unique and common & unique features in the
MSnSets used) as well as to submit features for selection. See
2.7. data for further details.
Fig. 1: Vignette of
The tab PCA is characterised by its main panel which shows a
PCA plot for the selected
MSnSet in the case of
and two PCA plots for
pRolocVis. The sidebar panel is divided into
Display selection and Plot.
Fig. 2: Appearance of PCA tab for
pRolocComp the plot whose appearance is going to altered has to be selected
by selecting the appropriate radio button left of the name of
MSnSet instance in the sidebar panel.
pRolocComp offers the possibility to mirror the PCA plot of the
second object. By clicking on
x-axis below mirror 2nd object features
are mirrored along the x-axis, while clicking on
y-axis mirrors along the
y-axis. This may be important when you compare experiments whose PCA analysis
have different signs.
Fig. 3: Radio buttons to select
object is a named list with
The manipulation of the plots works the same way for
pRolocVis and for
The Display selection widget is described below. The
Plot compartment enables to adjust the appearance of the PCA plot
in the main panel. We are able to colour features (proteins) in
matters of common properties by changing the drop-down list
colour. These properties are the
variables. For example if we upload the
andy2011 data set in
and select the colour
markers, the features in the PCA plot will be coloured
according to their organelle affiliation. As soon as we select another
none, two (or three) new items will be added to the
(1) symbol type: By selecting one of the feature variables of the
MSnSet in the drop-down list of symbol type the symbol type of
the features in the plot will be changed.
(2) legend and position of legend: By clicking on the check box to the left of legend a legend is added to the plot and by choosing one of the items in the drop-down list position of legend below its position will be changed.
(3) point size: This drop-down list might appear when numeric feature variable have been identified. The default 1 allows for an unaltered display of the plot, while selecting other items in the list renders the features in the PCA plot according to their numerical value in the variable label (for example classification scores).
Fig. 4: Appearance of PCA tab (
used for colours, legend added.
By changing the drop-down lists of the items PC along x axis and PC along y axis the x-values and y-values, respectively, the plot will be rendered according to the new principal components.
To zoom in and out drag and drop the little arrows of the slider of the items zoom x-axis and zoom y-axis. This may be of great help when you want to identify points in dense clusters.
By clicking on Download Plot in the main panel below the PCA plot will open a dialog window with an interface on showing or saving the PCA plot as it is displayed in the main panel.
pRolocVis the tab protein profiles shows the protein profiles in
the main panel (with an option of exporting the plot as it is shown in the main
panel by clicking on the button Download Plot) - for
pRolocComp it shows
the plots for the two
MSnSet instances (the corresponding plot(s) for the
first element in the list will be displayed on the left,
for the second element on the right). In the sidebar panel there is the
Display selection widget and the Plot widget.
Have a look on section 3. Display selection widget if you want to retrieve information about how to use the Display selection widget.
The Plot widget helps to manipulate the plots shown in the main
pRolocComp one has first to select the appropriate
radio button next to the
MSnSet instance in the sidebar
panel). Let's assume we want to have a look upon the protein profiles
for the proteins from which we know that they belong to the organelles
Endoplasmic reticulum, the Golgi apparatus, Mitochondrion and the
plasma membrane for the
andy2011 MSnSet. This is done in
works in the same way in
pRolocComp. We have four organelles to look
at, so we select
pRolocComp there is either the possibility to
2 plots per
MSnSet) in the drop-down list
number of plots to display. We will select the feature variable
markers in the drop-down list feature(s) in and select
(coding for Endoplasmic reticulum)
in the drop-down list underneath (assigned to). To
display the next plot we have to change the slider Selected plot
to position 2. Accordingly to our question we will
change the second drop-down list to
Golgi (coding for Golgi apparatus). We
proceed with the two remaining organelles as described before by
changing firstly the slider to the next position and by changing the
drop-down lists accordingly to the organelles we want to
display. Please be aware that it is possible to "go" back to a plot to
change its parameter.
Fig. 5: Appearance of protein profiles tab in
showing protein profiles of organelles/compartments
Endoplasmic reticulum, Golgi apparatus, Mitochondrion and plasma
membrane of markers (
The tab quantitation displays the quantitation data for the proteins as a data table.
In the main panel you can change the number of proteins shown per page and search both for proteins (or for the quantitation data). Also, you may sort the proteins by name or the quantitation data by clicking on the arrows on the top of the data table.
In the sidebar panel the Display selection widget is located as well as
radio buttons to display all data or just selected features
(see 3. Display selection for further details). In
there is also another well panel to select the appropriate
radio button next to the name of the
MSnSet to show the
respective quantitation data.
Fig. 6: Appearance of quantitation tab
pRolocVis. Features shown originate from selection made in
the PCA and protein profiles plots
The tab feature meta-data displays the feature meta-data for the proteins as a data table.
The layout of the tab is similar to the quantitation tab
and allows for sorting and querying the feature meta-data of the
The sidebar comprises the Display selection widget and radio buttons to
show all or only selected features (see 3. Display selection
for further details). In
pRolocComp there is in addition a set of two
radio buttons which allow to switch the
thus, the feature meta-data will be rendered to the selected
Fig. 7: Appearance of feature meta-data tab
pRolocVis. Features shown originate from selection made in
protein profiles plot
The tab sample meta-data displays the sample meta-data for the experiment, the name of the isotopes used for tagging and the associated fractions.
pRolocComp select the appropriate radio button next to
the object name in sidebar panel to display the corresponding sample meta-data.
Fig. 8: Appearance of sample meta-data tab
The appearance and operation are identical for
pRolocComp allow to use past search results to display in the
PCA plot, protein profiles and in the tabs quantitation and
feature meta-data (see 3. Display selection
for further details if this is your intention).
This ability requires the object
pRolocGUI_SearchResults in the global environment which is of
?FeaturesOfInterest in the console for further details).
In case this objects exists it will automatically be loaded to
pRolocComp and its content is displayed in the tab search.
Use the drop-down list in the main panel to browse through the
different features of the
FoICollection. To select features and display them
in multiple tabs add them to the field in the multiple drow-down list.
If no object called
pRolocGUI_SearchResults exists in the global
environment you still have the possibility to assign
FoICollection which will be assigned to the global environment when
To save features of interest to the object internally you need
to select features and add these to the
FoICollection by entering an
appropriate description in the text field (on the sidebar panel, which will
be useful to trace back to the underlying features and does not exist yet in
FoICollection). Add the selected features to the object
pRolocGUI_SearchResults in the global environment by clicking on
Create new features of interest. You only have the possibility to
add selected features to the
FoICollection when you have entered an
appropriate description, i.e. one that doesn't exist yet in the
FoICollection and if you have selected
the button does not show up in the application.
FoICollection will be assigned to
pRolocGUI_SearchResults in the global environment.
To create an example object
pRolocGUI_SearchResults containing the
first ten features of
tan2009r1 run the following commands in the console.
Both traceable and non-traceable
data(tan2009r1, package = "pRolocdata") pRolocGUI_SearchResults <- FoICollection() newFeat <- FeaturesOfInterest(description = "test_01", fnames = featureNames(tan2009r1)[1:10], object = tan2009r1) pRolocGUI_SearchResults <- addFeaturesOfInterest(newFeat, pRolocGUI_SearchResults)
Fig. 9: Appearance of search tab (
pRolocVis. Search result
pRolocVis_Test1 contains one feature of interest
The tab data is the last tab for