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

作者信息

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

机构信息

Lawrence Livermore National Laboratory, Livermore, CA, USA.

出版信息

Bioinformatics. 2005 Oct 1;21(19):3733-40. doi: 10.1093/bioinformatics/bti612. Epub 2005 Aug 9.

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.

摘要

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