Department of Bioinformatics and Computational Biology

SuperCurve:Overview

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SuperCurve

SuperCurve
Overview
Description SuperCurve is a suite of R packages which can be used as a tool for curve fitting analysis of gene expression microarray data.
Development Information
Language R,Tcl/Tk
Current Version 1.5.15
Platforms Un*x (including OS X)/Windows
License Artistic 2.0
Status Active
Last Updated 2015-08-02
References
Citations Publications Not Provided
News Around mid 2014, the SuperCurve packages were migrated to R-Forge, available here.
Help and Support
Contact Paul Roebuck


SuperCurve is a suite of R packages which can be used as a tool for curve fitting analysis of gene expression microarray data. One of the packages perform the core functionality, while two others providing graphical user interfaces. The primary user interface, SuperCurveGUI, allows the user the ability to interact directly with the various settings available in order to run an analysis, and to receive visual output of the slide(s) and related plots.

Contents


Packages

SuperCurve
R package for analyzing RPPAs
SuperCurveGUI
Tcl/Tk GUI front end for the SuperCurve R package
SlideDesignerGUI
SlideDesignerGUI is a graphical tool to allow researchers to describe the location and concentration of different positive and negative controls on a reverse phase protein array

System Requirements

The SuperCurve R package requires R 2.15.0 or later to run.

We also recommend having ImageMagick installed for optimal functionality. This is because the SuperCurve package requires the *convert* binary from the ImageMagick software suite in order to produce its merged graph/slide image JPEG output. Without ImageMagick, individual plots will still be generated, but they will not be merged together into a single image.

Download and install the software, if necessary. Ensure that the binary can be invoked from the PATH environment variable. After issuing the following command from a terminal, the output should match if configured correctly.

$ convert --version | grep -o ImageMagick | uniq
ImageMagick
$ _

Installation

From within an R session, type the following:

  1. Load the utilities library.
library(utils)
  1. Add several repositories to the default R repository list.
options(repos=c(getOption("repos"),
                local({
                    rforge <- "http://r-forge.r-project.org"
                    names(rforge) <- "R-Forge"
                    rforge
                }),
                local({
                      rvers <- getRversion()
                      repos.hostname <- "bioinformatics.mdanderson.org"
                      oompa <- sprintf("http://%s/OOMPA/%s",
                                       repos.hostname,
                                       paste(rvers$maj, rvers$min, sep="."))
                      names(oompa) <- "OOMPA"
                      oompadevel <- sprintf("http://%s/OOMPA-devel",
                                            repos.hostname)
                      names(oompadevel) <- "OOMPA-devel"
                      c(oompadevel, oompa)
                })))                                  
  1. Update existing packages before installing more.
update.packages(ask=FALSE)                                     
  1. Install prerequisite packages.
prereq.pkgs <- c("boot",
                 "cobs",
                 "mgcv",
                 "quantreg",
                 "robustbase",
                 "splines",
                 "timeDate")

install.packages(prereq.pkgs, dependencies=TRUE)
  1. Install SuperCurve packages.
supercurve.pkgs <- c("tclish",
                     "SlideDesignerGUI",
                     "SuperCurve",
                     "SuperCurveGUI")

install.packages(supercurve.pkgs, dependencies=TRUE)

Assuming everything went okay, the SuperCurve-related packages and their dependencies should now be installed.

Documentation

You can find a detailed SuperCurveGUI user's guide here.

Release History

On 03 April 2011, the following packages were promoted to production status. The production releases can be obtained from the OOMPA R repository.

  • SuperCurve 1.4.0
  • SuperCurveGUI 2.0.0
  • SlideDesignerGUI 1.4.0

Support

For Frequently Asked Questions, Bug Reports, and other concerns, please visit the forum at this link

Credits

References

Hu, J., He, X., Baggerly, K., Coombes, K., Hennessy, B., & Mills, G. (2007).
Non-parametric Quantification of Protein Lysate Arrays.
Bioinformatics 23(15), 1986-1994.
doi:10.1093/bioinformatics/btm283

Neeley, S., Kornblau, S., Coombes, K., & Baggerly, K. (2009).
Variable Slope Normalization of Reverse Phase Protein Arrays
Bioinformatics 25(11), 1384-1389.
doi:10.1093/bioinformatics/btp174

Neeley, S., Baggerly, K., & Kornblau, S. (2010).
Surface Adjustment of Reverse Phase Protein Arrays Using Positive Control Spots
Cancer Informatics 11, 77-86.
doi:10.4137/cin.s9055

Ju, Z., Liu, W., Roebuck, P., Siwak, D., Zhang, N., Lu, Y., Davies, M., Akbani, R., Weinstein, J., Mills, G., & Coombes, K. (2015).
A Robust Classifier for the Quality Control of Reverse Phase Protein Arrays
Bioinformatics 31(6), 912-918.
doi:10.1093/bioinformatics/btu736