Analysis of the real EADGENE data set: comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (open access publication).

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Jaffrézic, F; de Koning, D-J; Boettcher, PJ; Bonnet, A; Buitenhuis, B; Closset, R; Déjean, S; Delmas, C; Detilleux, JC; Dovc, P; Duval, M; Foulley, J-L; Hedegaard, J; Hornshøj, H; Hulsegge, I; Janss, L; Jensen, K; Jiang, L; Lavric, M; Lê Cao, K-A; Lund, MS; Malinverni, R; Marot, G; Nie, H; Petzl, W; Pool, MH; Robert-Granié, C; San Cristobal, M; van Schothorst, EM; Schuberth, H-J; Sørensen, P; Stella, A; Tosser-Klopp, G; Waddington, D; Watson, M; Yang, W; Zerbe, H; Seyfert, H-M

Published Date

  • November 2007

Published In

Volume / Issue

  • 39 / 6

Start / End Page

  • 633 - 650

PubMed ID

  • 18053573

Pubmed Central ID

  • PMC2682811

International Standard Serial Number (ISSN)

  • 0999-193X

Digital Object Identifier (DOI)

  • 10.1186/1297-9686-39-6-633


  • eng

Conference Location

  • France