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The EADGENE Microarray Data Analysis Workshop (Open Access publication)

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Author(s): de Koning Dirk-Jan | Jaffrézic Florence | Lund Mogens | Watson Michael | Channing Caroline | Hulsegge Ina | Pool Marco | Buitenhuis Bart | Hedegaard Jakob | Hornshøj Henrik | Jiang Li | Sørensen Peter | Marot Guillemette | Delmas Céline | Cao Kim-Anh | San Cristobal Magali | Baron Michael | Malinverni Roberto | Stella Alessandra | Brunner Ronald | Seyfert Hans-Martin | Jensen Kirsty | Mouzaki Daphne | Waddington David | Jiménez-Marín Ángeles | Pérez-Alegre Mónica | Pérez-Reinado Eva | Closset Rodrigue | Detilleux Johanne | Dovč Peter | Lavrič Miha | Nie Haisheng | Janss Luc

Journal: Genetics Selection Evolution
ISSN 0999-193X

Volume: 39;
Issue: 6;
Start page: 621;
Date: 2007;
Original page

Keywords: gene expression | two colour microarray | statistical analysis

ABSTRACT
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.
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Tango Rapperswil
Tango Rapperswil