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Bioinformatics Advance Access published online on August 9, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti612
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received June 15, 2005
Revised July 5, 2005
Accepted August 2, 2005

Article

Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using DeCyderTM

Imola K. Fodor 1*, David O. Nelson 1, Michelle Alegria-Hartman 2, Kristin Robbins 2, Richard G. Langlois 2, Kenneth W. Turteltaub 2, Todd H. Corzett 2, and Sandra L. McCutchen-Maloney 2

1 Computation Directorate, Lawrence Livermore National Laboratory, Livermore CA
2 Biosciences Directorate, Lawrence Livermore National Laboratory, Livermore CA

* To whom correspondence should be addressed.
Imola K. Fodor, E-mail: fodor1{at}llnl.gov


  Abstract

Motivation: The DeCyder software (GE Healthcare) is the current state-of-the-art commercial product for the analysis of two-dimensional difference gel electrophoresis (2-D DIGE) experiments. Analyses complementing DeCyder are suggested by incorporating recent advances from the microarray data analysis literature. A case study on the effect of smallpox vaccination is used to compare the results obtained from DeCyder to the results obtained by applying moderated t-tests adjusted for multiple comparisons to DeCyder output data that was additionally normalized.

Results: Application of the more stringent statistical tests applied to the normalized 2-D DIGE data decreased the number of potentially differentially expressed proteins from the number obtained from DeCyder, and increased the confidence in detecting differential expression in human clinical studies.

Availability: The marray and limma packages used here are available from http://www.bioconductor.org/.


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