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Bioinformatics Advance Access originally published online on August 9, 2005
Bioinformatics 2005 21(19):3733-3740; 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{at}oxfordjournals.org

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

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

*To whom correspondence should be addressed.

Motivation: The DeCyder software (GE Healthcare) is the current state-of-the-art commercial product for the analysis of two-dimensional difference gel electrophoresis (2D 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 with 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 2D 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/

Contact: fodor1{at}llnl.gov

Received on June 15, 2005; revised on July 5, 2005; accepted on August 2, 2005

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