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

Imola K. Fodor, David O. Nelson, Michelle Alegria-Hartman, Kristin R Hoffman, Richard G. Langlois, Ken W Turteltaub, Todd H. Corzett, Sandra L. McCutchen-Maloney

Research output: Contribution to journalArticlepeer-review

59 Scopus citations

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 (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.

Original languageEnglish (US)
Pages (from-to)3733-3740
Number of pages8
JournalBioinformatics
Volume21
Issue number19
DOIs
StatePublished - Oct 2005
Externally publishedYes

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

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