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Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)

Author(s): Jaffrézic Florence | de Koning Dirk-Jan | Boettcher Paul | Bonnet Agnès | Buitenhuis Bart | Closset Rodrigue | Déjean Sébastien | Delmas Céline | Detilleux Johanne | Dovč Peter | Duval Mylène | Foulley Jean-Louis | Hedegaard Jakob | Hornshøj Henrik | Hulsegge Ina | Janss Luc | Jensen Kirsty | Jiang Li | Lavrič Miha | Cao Kim-Anh | Lund Mogens | Malinverni Roberto | Marot Guillemette | Nie Haisheng | Petzl Wolfram | Pool Marco | Robert-Granié Christèle | San Cristobal Magali | van Schothorst Evert | Schuberth Hans-Joachim | Sørensen Peter | Stella Alessandra | Tosser-Klopp Gwenola | Waddington David | Watson Michael | Yang Wei | Zerbe Holm | Seyfert Hans-Martin

Journal: Genetics Selection Evolution
ISSN 0999-193X

Volume: 39;
Issue: 6;
Start page: 633;
Date: 2007;
Original page

Keywords: quality control | differentially expressed genes | mastitis resistance | microarray data | normalisation

Abstract A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.
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