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The Use of Open Source Bioinformatics Tools to Dissect Transcriptomic Data

Part of the Methods in Molecular Biology book series (MIMB,volume 835)

Abstract

Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.

We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

Key words

  • Filamentous fungi
  • Microarray
  • Transcriptomics
  • Expression profiling
  • Bioconductor
  • Gene coexpression networks

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Acknowledgments

This work was supported by a grant of SenterNovem IOP Genomics project IGE07008. Part of this work was carried out within the research program of the Kluyver Centre for Genomics of Industrial Fermentation, which is part of the Netherlands Genomics Initiative/Netherlands Organization for Scientific Research. We thank T.G. Homan for discussions and proof reading of the manuscript.

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Correspondence to Vera Meyer .

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Nitsche, B.M., Ram, A.F.J., Meyer, V. (2012). The Use of Open Source Bioinformatics Tools to Dissect Transcriptomic Data. In: Bolton, M., Thomma, B. (eds) Plant Fungal Pathogens. Methods in Molecular Biology, vol 835. Humana Press. https://doi.org/10.1007/978-1-61779-501-5_19

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  • DOI: https://doi.org/10.1007/978-1-61779-501-5_19

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