Developing R Graphical User Interfaces

Setia Pramana

Medical Epidemiology and Biostatistics Department

Karolinska Institutet, Stockholm, Sweden

Outlines

• Motivations• R GUI

• IsoGeneGUI• neaGUI

• How to develop an R GUI?• Independent GUI• Embedded GUI

(RcmdrPlugin.BiclustGUI)• Summary

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R Pros and Con

Free open source and widely used. Can be integrated with other languages

(C/C++, Java). R can interact with many data sources

and other statistical packages (SAS, Stata, SPSS, and Minitab).

For the high performance computing task multiple cores, either on a single machine or across a network.

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R: A Command line interface (CLI)

Users type commands to perform a statistical analysis.

Is preferred for advanced users allows direct control, more accurate, flexible and the analysis is reproducible.

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R: A Command line interface (CLI)

Requires good knowledge of the language difficult for beginners or less frequent users.

R provides tools for building GUIs RGUI

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Graphical User Interface (GUI)

A tool to provide an event-driven user interface.

An extra layer between the user and the program

Based on menus, dialog boxes, icons and controls.

Window, icon, menu, and pointing device (WIMP) paradigm

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R GUI Projects

Integrated development environment (IDE)/Script Editors aimed to provide feature-rich environments to edit R scripts and code: Rstudio (www.rstudio.com), and architect (www.Openanalytics.eu)

Web based application: the Rweb (Banfield, 1999), R.Net (www.u.arizona.edu

/~ryckman/Net.php), or gWidgetsWWW (Verzani, 2012).

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R GUI Projects

Python: OpenMeta-Analyst (Wallace et al, 2012)

Java: JGR (Java GUI for R), Deducer (Fellows, 2012), and Glotaran (Snellenburg, 2012).

Php: R-php (http://dssm.unipa.it/R-php/) Other extensions connect R to graphical

toolboxes for developing menus and dialog boxes: Tcltk, Gtk.

Today, we focus on Tcltk 04/12/2023 8

R GUI Tcl/Tk

Most commonly used: easy, no additional software needed and ready to be used in R (tcltk package)

R-Tcl/Tk interface from the tcltk package (Dalgaard, 2001 and Welch, 2000).

The tcltk package allows the use of the Tk (toolkit) graphical user interface elements within R by embedding Tk commands into the R language. 04/12/2023 9

R GUI Tcl/Tk

R GUIs developed by using tcl/tk or RGtk:• LimmaGUI (Wettenhall and Smyth,

2004),• LMMNorm (Haldermans, 2010), • IsoGeneGUI (Pramana et al. , 2010,

2012)• NeaGUI (Pramana et.al, 2013)• Rcommander (Fox, 2005)• RcmdrPlugin.biclustGUI (Pramana, 2011)04/12/2023 10

R GUI Tcl/Tk

Independent GUI

R GUI Tcl/Tk

Embeded GUI

IsoGeneGUI

To perform dose response microarray analysis in early drug development.

Identify genes with a monotonic trend in the expression levels with respect to the increasing doses

CLI based: IsoGene package (Pramana,2010)

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IsoGeneGUI

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Main window of IsoGeneGUI

IsoGeneGUI: Isotonic Regression Plot

Command line:IsoPlot(dose, express , type="ordinal", add.curve=TRUE)

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IsoGeneGUI: Isotonic Regression Plot

Command line:IsoPlot(dose, express , type="ordinal", add.curve=TRUE)

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IsoGeneGUI: Significant Analysis Microarray

qqstat <- Isoqqstat(x, y, fudge="pooled", niter=50)allfdr <- Isoallfdr(qqstat, , stat = "E2")IsoSAMPlot(qqstat, allfdr, FDR = 0.1, stat = "E2")SAM.Res <- IsoTestSAM(x, y, fudge="pooled", niter=50, FDR=0.05, stat="E2")

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IsoGeneGUI: Significant Analysis Microarray

qqstat <- Isoqqstat(x, y, fudge="pooled", niter=50)allfdr <- Isoallfdr(qqstat, , stat = "E2")IsoSAMPlot(qqstat, allfdr, FDR = 0.1, stat = "E2")SAM.Res <- IsoTestSAM(x, y, fudge="pooled", niter=50, FDR=0.05, stat="E2")

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IsoGeneGUI Manual Guide

IsoGeneGUI help: htlm

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Vignette: http://www.bioconductor.org/packages/2.11/bioc/vignettes/IsoGeneGUI/inst/doc/IsoGeneGUI.pdf

Users’ manual: http://www.ibiostat.be/software/IsoGeneGUI/files/IsoGeneGUI%20users'%20manual.pdf

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neaGUI

To help interpretation of differentially expressed (DE) genes in context of biological processes, pathways and networks.

Perform network enrichment analysis.

Input: DE genes Output: enriched

pathways statistics based on gene interaction networks. 04/12/2023 22

neaGUI Output

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neaGUI Output

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RGUI, How to Build One?

Choose one of RGUI categories, and tools to be used (tcltk, java, etc.) which suit with the package purpose.

Make sketches of the window box and consider:• Input • Options• Output

Can all functions be run in a single window (e.g. neaGUI)? Or a main window with menu (IsoGeneGUI) and separate dialog boxes are needed? 04/12/2023 25

Create Main Window

tt <- tktoplevel()tkwm.title(tt,"My New GUI")topMenu <- tkmenu(tt)tkconfigure (tt,menu=topMenu)fileMenu <- tkmenu(topMenu,tearoff=FALSE)openMenu <- tkmenu(topMenu,tearoff=FALSE)tkadd(openMenu,"command",label="xls file", command= getXls)tkadd(openMenu,"command",label="text file”)

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Create Main Window

tt <- tktoplevel()tkwm.title(tt,"My New GUI")topMenu <- tkmenu(tt)tkconfigure (tt,menu=topMenu)fileMenu <- tkmenu(topMenu,tearoff=FALSE)openMenu <- tkmenu(topMenu,tearoff=FALSE)tkadd(openMenu,"command",label="xls file", command= getXls)tkadd(openMenu,"command",label="text file”)

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getXls <- function () { fileName <- tclvalue(tkgetOpenFile(filetypes= gettext(' {"Excel Files" {".xls"}} {"All Files" {"*"}}')))data <- get( fileName) }

Create Main Window

tt <- tktoplevel()tkwm.title(tt,"My New GUI")topMenu <- tkmenu(tt)tkconfigure (tt,menu=topMenu)fileMenu <- tkmenu(topMenu,tearoff=FALSE)openMenu <- tkmenu(topMenu,tearoff=FALSE)tkadd(openMenu,"command",label="xls file", command= getXls)tkadd(openMenu,"command",label="text file")tkadd(fileMenu,"cascade",label="Open data",

menu=openMenu)tkadd(fileMenu,"cascade",label="Edit data")

tkadd(fileMenu,"command",label="Quit",command=function() tkdestroy(tt))tkadd(topMenu,"cascade",label="File",menu=fileMenu)tkadd(topMenu,"cascade",label="Help")tkfocus(tt)

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Create a Dialog Box

Create the windowrequire(tcltk)tt<-tktoplevel()tkwm.title(tt,"Input Window")

Edit BoxName <- tclVar("")entry.Name <-tkentry(tt,width="20", textvariable=Name)tkgrid(tklabel(tt,text="Name:"), entry.Name)

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Create a Dialog Box

Radio buttonrb1 <- tkradiobutton(tt)rb2 <- tkradiobutton(tt)rbValue <- tclVar("Male")tkconfigure(rb1,variable=rbValue,

value="Male")tkconfigure(rb2,variable=rbValue,

value="Female")tkgrid(tklabel(tt,text="Sex:"))tkgrid(tklabel(tt,text="Male"),rb1)tkgrid(tklabel(tt,text="Female"),rb2)

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Create a Dialog Box

List box with scroll barscr <- tkscrollbar(tt, repeatinterval=5, command=function(...) tkyview(tl,...))tl<-tklistbox(tt,height=4,selectmode="single", background="white")tkgrid(tklabel(tt,text="City:"), tl, scr)city <- c("Brussels","Jakarta", "London", "Stockholm")for (i in (1:4)) tkinsert(tl,"end",city [i]) tkselection.set(tl,1) tkgrid.configure(scr,rowspan=4,sticky="nsw")

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Create a Dialog Box

OK buttonOK.but <-tkbutton(tt,text=" OK ", command=OnOK)tkgrid(OK.but)tkgrid.configure(OK.but)tkfocus(tt)

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Run the function (OK button)

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Run the function (OK button)

OnOK <- function() { NameVal <- tclvalue(Name) rbVal <- as.character(tclvalue (rbValue)) if (rbVal=="Male") pref = "Mr." if (rbVal=="Female") pref = "Mrs.“ cityChoice <- city [as.numeric(tkcurselection(tl))+1] tkdestroy(tt) msg <- paste("Good morning ",pref , NameVal , "from", cityChoice, sep=" ") tkmessageBox(message=msg)}

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Embeded R GUI: Rcmdr Plugin

GUIs that are embedded/attached into another GUI, i.e., R Commander (Rcmdr)

Rcmdr was originally developed as a basic-statistics graphical user interface (“GUI”) to R.

Rcmdr needs extension for specific statistical analysis

More than 20 Rcmdr plugins today

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Rcmdr Plugin Advantages

Does not need to develop GUI for common procedures: Open, save and manipulate data.

Can use standard statistical analysis. In term of programming: easier

(standard tcltk commands are provided) Users know how to work in command

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R Commander (Rcmdr)

Developed by John Fox from McMaster University, Canada.

Not only providing GUIs but also rendering users to R commands

Advantages:• Ease of use. Beginners will have less

problem to start to use Rcmdr.• Coverage. Offers wide range of basic

statistics analysis and data management.

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R Commander (Rcmdr)

Advantages:• Cross-platform functionality. Primarily under

Windows, but also available in Linux and Macintosh OS/X.

• Extensibility: one can develop “plug-in" packages for new methods/analysis.

• Protects the novices from errors. Limited options related to the current context will minimize the errors made by users.

• Exposes users to R commands.

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R Commander

Main Window: Script

Window Output

Window Messages

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RcmdrPlugin.biclustGUI

An extension for the Rcmdr for biclustering analysis.

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Standard Rcmdr Menu

An extension for the Rcmdr for biclustering analysis.

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Standard Rcmdr MenuRcmdr with biclustering plugin

Create a Dialog Box

initializeDialog(title = gettextRcmdr("Biclustering-CC"))specFrame <- tkframe(top, borderwidth=5)tkgrid(labelRcmdr(specFrame , text=gettextRcmdr("CC Specification:")))

deltaVal <- tclVar(“ ")deltaField <- ttkentry(specFrame, width = "5",textvariable = deltaVal )tkgrid(labelRcmdr(specFrame , text=gettextRcmdr("Delta:")), deltaField)

alphaVal <- tclVar("2")alphaField <- ttkentry(specFrame, width = "5",textvariable = alphaVal )tkgrid(labelRcmdr(specFrame , text=gettextRcmdr("Alpha:")), alphaField)

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Create a Dialog Box

numberVal <- tclVar("100")numberField <- ttkentry(specFrame,

width = "5”, textvariable = numberVal)tkgrid(labelRcmdr(specFrame , text=gettextRcmdr("Maximal Numbers : ")), numberField)

OKbutton <- buttonRcmdr(specFrame , text = gettextRcmdr("Show Result"), width = "12", command = onOK, default = "active", borderwidth = 3)

tkgrid(OKbutton,Plotbutton ,exitButton ,helpButton) tkgrid(specFrame) dialogSuffix()

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Submitting the job (OK button)

onOK <- function() { .activeDataSet <- ActiveDataSet() delta <- paste(tclvalue(deltaVal )) alpha <- paste(tclvalue(alphaVal )) number <- if (tclvalue( numberVal) == "") "100“ else paste(tclvalue(numberVal)) doItAndPrint(paste("CCbics <-biclust(as.matrix(",.activeDataSet,"), method=BCCC(), delta=", delta, ", alpha= ", alpha, ", number= ",number ,")" , sep="") ) doItAndPrint("CCbics ") tkfocus(CommanderWindow())}

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doItAndPrint(paste("CCbics <-biclust(as.matrix(",.activeDataSet,"),method=BCCC(), delta=", delta, ", alpha= ", alpha, ", number= ",number ,")" , sep="") )

doItAndPrint("CCbics ")

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Output

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RcmdrPlugin: Menu-Definition File

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The plugin menus are defined the file: menus.txt.

The plugin menus are defined the file: menus.txt. The first line in menus.txt defines the top-level

biclustGUI menu:

Menu biclustMenu topMenu “ “ “ “ “ “ “ “

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biclustGUI menu:

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Define menu/item

biclustGUI menu:

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Name of new menu

biclustGUI menu:

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Parent of the menu

biclustGUI menu:

The second line in menus.txt defines a menu item under biclust menu:

item biclustMenu command "Biclustering Plaid " PlaidWin "" "packageAvailable ('RcmdrPlugin.BiclustGUI')"

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biclustGUI menu:

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Define menu item

biclustGUI menu:

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Menu item belongs to

biclustGUI menu:

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Menu item invokes a command

biclustGUI menu:

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Text displayed

biclustGUI menu:

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Called function

biclustGUI menu:

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Conditional activation and installation

Next Stage

Error handling: message boxes, warnings, etc. Trial by other people. Compile as a package. Submit in a repository for development we

can use R-forge. When all ready, submit to a repository,

Bioconductor, or CRAN. Bioconductor more restrict and have to comply

all guidelines: http://www.bioconductor.org/developers/package-guidelines/ 04/12/2023 60

Summary

A GUI could help novice R users for utilizing all the power of R.

Increase the use of our package/methods especially by scientists with no/less knowledge of R.

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Summary

A GUI could help novice R users for utilizing all the power of R.

Increase the use of our package/methods especially by scientists with no/less knowledge of R.

Things to consider in developing a GUI:• Type of GUI (spreadsheets, menu/dialog boxes),• Tool to develop (tcltk, java)• Embedded/Independent.• Single/Multi dialog boxes

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Summary

Independent GUI: really for a specific use, no need of “useless” capabilities, simpler.

Rcmdr PlugIn in: easier, all standard data manipulation and analysis is ready, users can learn the command.

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Summary

Independent GUI: really for a specific use, no need of “useless” capabilities, simpler.

Rcmdr PlugIn in: easier, all standard data manipulation and analysis is ready, users can learn the command.

Make sure GUI is simple and user friendly.

Design Development Trial Packaging and Storing

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The GUIs

IsoGeneGUI:http://www.bioconductor.org/packages/2.11/bioc/html/IsoGeneGUI.html

neaGUI: https://r-forge.r-project.org/projects/neagui/

biclustGUI: http://www.ibiostat.be/software/BiclustGUI/index.html

Examples of RGUI: • http://www.sciviews.org/_rgui/• http://bioinf.wehi.edu.au/~wettenhall/RTclTkExa

mples/

• http://setiopramono.wordpress.com/r-programming/

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Next Development:

Isogene RSB : Web based development using R Service Bus: http://www.openanalytics.eu/r-service-bus

R Service Bus: plug R into a processes independently of the technology used by other software applications involved in the workflow.

Web Based neaGUI using shiny Shiny: Easy web applications in R: http

://www.rstudio.com/shiny/

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RSB-IsoGene

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Web based neaGUI

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Collaborator

Karolinska Institutet, Sweden: Yudi Pawitan & Woojoo Lee Scilifelab, Sweden: Andrey Alexeyenko Johnson & Johnson Research and Development, Belgium: Luc

Bijnes & Willem Talloen. Hasselt University, Belgium: Ziv Shkedy, Dan Lin, Philippe H,

Martin O Pushpike, Tatsiana K. Open Analytics, Belgium: Tobias Verbeke Johannes Kepler University of Linz, Austria: Sepp Hochreiter’s

Group LMU Munich, Germany: Sebastian Kaiser

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Thank you for your attention…

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References

Pramana, S., Lin, D., and Shkedy Z., (2010), IsoGeneGUI Bioconductor Package Vignette.

Pramana, S., Lin, D., Haldermans, P., Shkedy Z., and Verbeke, T., De Bondt, A., Talloen, W., Göehlmann,. H and Bijnens, L. (2010). “IsoGene: An R Package for Analyzing Dose-response Studies in Microarray Experiments", R Journal 2/1.

Pramana, S., Lin, D., Haldermans P., and Verbeke, T. (2102). “A User Friendly Interface for Analyzing Dose-response Studies in Microarray Experiments: The IsoGene-GUI package”, in Lin, D., Shkedy, Z., Yekutieli, D., Amaratunga, D. and Bijnens L. (editors). Modeling Dose-response Microarray Data in Early Drug Development Experiments Using R, Springer.

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References

Pramana (2011) RcmdrPlugin.BiclustGUI: A User Friendly Interface for Biclustering Analysis, a chapter of PhD: “Statistical Methods for Microarray Experiments: Analysis Dose-response Studies and Software Development in R”, Hasselt University, Belgium.

Pramana, S., Lee, W., Alexeyenko, A., Pawitan., Y. (2012). neaGUI: A Graphical User Interface for Network Enrichment Analysis.

Fox J (2005). The R Commander: A Basic-Statistics Graphical User Interface to R." Journal of Statistical Software, 14(9), 1-42.

Valero-Mora, P.M and Ledesma R.D. (2012) “Graphical User Interfaces for R”. Journal of Statistical Software.

Verzani J (2007). An Introduction to gWidgets." R News, 7(3), 26-33.

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