Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using DeCyder
| Autor: | Michelle Alegria-Hartman, David O. Nelson, Todd H. Corzett, Kristin Robbins, Imola K. Fodor, Richard G. Langlois, Kenneth W. Turteltaub, Sandra L. McCutchen-Maloney |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Statistics and Probability
Proteome Computer science Difference gel electrophoresis Computational biology computer.software_genre Biochemistry Models Biological Humans Computer Simulation Electrophoresis Gel Two-Dimensional Molecular Biology Two-Dimensional Difference Gel Electrophoresis Models Statistical Gene Expression Profiling Blood Proteins Computer Science Applications Computational Mathematics Computational Theory and Mathematics Gene Expression Regulation Data Interpretation Statistical Data mining computer Algorithms Smallpox Vaccine Software |
| Zdroj: | Bioinformatics (Oxford, England). 21(19) |
| ISSN: | 1367-4803 |
| Popis: | 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: [email protected] |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|