Publication
Title
Alternative experimental design with an applied normalization scheme can improve statistical power in 2D-DIGE experiments
Author
Abstract
2D-DIGE experiments are a high-throughput technique for measuring protein abundances based on gel separation. Traditionally three samples are multiplexed per gel: two biological test samples and a third internal standard sample consisting of a pool of all test samples. We demonstrate that the use of an internal standard helps to account for technical variation caused by spatial intensity biases that exist in the gels and propose a novel data-preprocessing technique, a spatial intensity bias removal (SIBR), which can approximate these biases using only the data of biological replicates loaded on the gel. Using this technique we show that by replacing the internal standard with additional biological replicates, a significant increase in statistical power can be achieved compared to traditional 2D-DIGE designs. This boost in statistical power can be used to reduce the false positive rate for identifying differential protein abundances without compromising sensitivity, or to improve sensitivity without compromising false positive rate. A software implementation of SIBR can be downloaded at http://ibiza.biw.kuleuven.be/SIBR.
Language
English
Source (journal)
Journal of proteome research
Publication
2010
ISSN
1535-3893
Volume/pages
9:10(2010), p. 4919-4926
ISI
000282257800005
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 04.08.2010
Last edited 21.06.2017
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