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. 2007 Nov 15;39(6):621–631. doi: 10.1186/1297-9686-39-6-621

The EADGENE Microarray Data Analysis Workshop (Open Access publication)

Dirk-Jan de Koning 1,, Florence Jaffrézic 2, Mogens Sandø Lund 3, Michael Watson 4, Caroline Channing 1, Ina Hulsegge 5, Marco H Pool 5, Bart Buitenhuis 3, Jakob Hedegaard 3, Henrik Hornshøj 3, Li Jiang 3, Peter Sørensen 3, Guillemette Marot 2, Céline Delmas 6, Kim-Anh Lê Cao 6,7, Magali San Cristobal 6, Michael D Baron 8, Roberto Malinverni 9, Alessandra Stella 9, Ronald M Brunner 10, Hans-Martin Seyfert 10, Kirsty Jensen 1, Daphne Mouzaki 1, David Waddington 1, Ángeles Jiménez-Marín 11, Mónica Pérez-Alegre 11, Eva Pérez-Reinado 11, Rodrigue Closset 12, Johanne C Detilleux 1, Peter Dovč 13, Miha Lavrič 13, Haisheng Nie 14, Luc Janss 3
PMCID: PMC2682810  PMID: 18053572

Abstract

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.

Keywords: gene expression, two colour microarray, statistical analysis

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