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.

Highlights

  • The recent development of high throughput gene-expression technologies, such as microarrays, has given rise to a plethora of new research hypotheses and possibilities

  • Some points of consensus regarding data analysis as presented by those authors [2] were the following: (1) many methods exist for the pre-processing of two-colour microarrays, but there is no clear winner and none were discussed in detail; (2) using fold-change alone as a test for differential expression is inefficient; (3) false discovery rate is a good alternative to conventional multiple testing; and (4) unsupervised classification is overused and should be validated using re-sampling techniques

  • The workshop was organised through the EC-funded network of excellence (NoE) EADGENE (European Animal Disease Genetics Network of Excellence for Animal Health and Food Safety; http://www.eadgene.info/)

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Summary

INTRODUCTION

The recent development of high throughput gene-expression technologies, such as microarrays, has given rise to a plethora of new research hypotheses and possibilities. Allison et al outline the areas of consensus and outstanding questions with regards to microarray analysis [2]. Given the lack of consensus in many areas, especially for the two-colour arrays that are abundant in livestock research, we organised a workshop on the analysis of microarrays. Conferences dealing with the statistical analyses of microarrays using common sets of data have been successfully organised annually in the United States since 2000 [10] (http://www.camda.duke.edu/). These conferences have been large scale events, attracting 250 or more participants. The workshop was organised through the EC-funded network of excellence (NoE) EADGENE (European Animal Disease Genetics Network of Excellence for Animal Health and Food Safety; http://www.eadgene.info/)

WORKSHOP GOALS
THE WORKSHOP PARTICIPANTS
Real data
Simulated data
Differences between real and simulated data
Recommendations
CONCLUSIONS

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