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Comparison of different approaches for comparative genetic analysis using microarray hybridization

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Abstract

A robust analysis of comparative genomic microarray data is critical for meaningful genomic comparison studies. In this paper, we compare our method (implemented in a new software tool, GENCOM, freely available at http://www.ifr.ac.uk/safety/gencom) with three commonly used analysis methods: GACK (freely available at http://falkow.stanford.edu), an empirical cut-off value of twofold difference between the fluorescence intensities after LOWESS normalization or after AVERAGE normalization in which the fluorescence intensity is divided by the average fluorescence intensity of the entire data set. Each method was tested using data sets from real experiments with prior knowledge of conserved and divergent genes. GENCOM and GACK were superior when a high proportion of genes were divergent. GENCOM was the most suitable method for the data set in which the relationship between the fluorescence intensities was not linear. GENCOM has proved robust in an analysis of all the data sets tested.

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Acknowledgements

We gratefully acknowledge support from the BBSRC core strategic grants 434.1213A and 4311209A. JMW also wishes to acknowledge support from EC project TCS-TARGETS QLK2-CT-2000-00543.

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Author notes

  1. Lorna Friis

    Present address: Department of Medical Microbiology and Immunology, University of Alberta, Edmonton, Alberta, T6G 2H7, Canada

  2. Jerry Wells

    Present address: Swammerdam Institute for Life Sciences, University of Amsterdam, Nieuwe Achtergracht 166, Amsterdam, 1018 WV, Netherlands

Authors and Affiliations

  1. Institute of Food Research, Norwich Research Park, Coloney Lane, Norwich, NR4 7UA, UK

    Carmen Pin, Mark Reuter, Bruce Pearson, Karin Overweg & József Baranyi

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  1. Carmen Pin
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  2. Mark Reuter
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  6. József Baranyi
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  7. Jerry Wells
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Correspondence to Carmen Pin.

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Pin, C., Reuter, M., Pearson, B. et al. Comparison of different approaches for comparative genetic analysis using microarray hybridization. Appl Microbiol Biotechnol 72, 852–859 (2006). https://doi.org/10.1007/s00253-006-0536-x

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  • DOI: https://doi.org/10.1007/s00253-006-0536-x

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