Journal article
Analysis of a simulated microarray dataset: Comparison of methods for data normalisation and detection of differential expression (Open Access publication)
M Watson, M Pérez-Alegre, MD Baron, C Delmas, P Dovč, M Duval, JL Foulley, JJ Garrido-Pavón, I Hulsegge, F Jaffrézic, A Jiménez-Marín, M Lavrič, KA Lê Cao, G Marot, D Mouzaki, MH Pool, C Robert-Granié, M San Cristobal, G Tosser-Klopp, D Waddington Show all
Genetics Selection Evolution | EDP SCIENCES S A | Published : 2007
DOI: 10.1051/gse:2007031
Abstract
Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as..
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Awarded by Biotechnology and Biological Sciences Research Council