Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using DeCyder.
BACKGROUND
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.
Fodor
Imola K
IK
Lawrence Livermore National Laboratory, Livermore, CA, USA. fodor1@llnl.gov
Nelson
David O
DO
Alegria-Hartman
Michelle
M
Robbins
Kristin
K
Langlois
Richard G
RG
Turteltaub
Kenneth W
KW
Corzett
Todd H
TH
McCutchen-Maloney
Sandra L
SL
D000465:Algorithms; D001798:Blood Proteins / Q000032:analysis*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015180:Electrophoresis, Gel, Two-Dimensional / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000187:drug effects*; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D020543:Proteome / Q000032:analysis*; D012900:Smallpox Vaccine / Q000008:administration & dosage*; D012984:Software
D001798:Blood Proteins; D020543:Proteome; D012900:Smallpox Vaccine