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Robin: An Intuitive Wizard Application for R-Based Expression Microarray Quality Assessment and Analysis

MPS-Authors
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Lohse,  M.
Integrative Carbon Biology, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Nunes-Nesi,  A.
Central Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

/persons/resource/persons97255

Krueger,  P.
BioinformaticsCIG, Infrastructure Groups and Service Units, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Nagel,  A.
Integrative Carbon Biology, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Hannemann,  J.
Integrative Carbon Biology, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Giorgi,  F. M.
Integrative Carbon Biology, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Childs,  L.
BioinformaticsCIG, Infrastructure Groups and Service Units, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Osorio,  S.
Central Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Walther,  D.
BioinformaticsCIG, Infrastructure Groups and Service Units, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Selbig,  J.
BioinformaticsCRG, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Stitt,  M.
System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Fernie,  A. R.
Central Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Usadel,  B.
Integrative Carbon Biology, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Citation

Lohse, M., Nunes-Nesi, A., Krueger, P., Nagel, A., Hannemann, J., Giorgi, F. M., et al. (2010). Robin: An Intuitive Wizard Application for R-Based Expression Microarray Quality Assessment and Analysis. Plant Physiology, 153(2), 642-651. doi:10.1104/pp.109.152553.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0014-23BA-6
Abstract
The wide application of high-throughput transcriptomics using microarrays has generated a plethora of technical platforms, data repositories, and sophisticated statistical analysis methods, leaving the individual scientist with the problem of choosing the appropriate approach to address a biological question. Several software applications that provide a rich environment for microarray analysis and data storage are available (e.g. GeneSpring, EMMA2), but these are mostly commercial or require an advanced informatics infrastructure. There is a need for a noncommercial, easy-to-use graphical application that aids the lab researcher to find the proper method to analyze microarray data, without this requiring expert understanding of the complex underlying statistics, or programming skills. We have developed Robin, a Java-based graphical wizard application that harnesses the advanced statistical analysis functions of the R/BioConductor project. Robin implements streamlined workflows that guide the user through all steps of two-color, single-color, or Affymetrix microarray analysis. It provides functions for thorough quality assessment of the data and automatically generates warnings to notify the user of potential outliers, low-quality chips, or low statistical power. The results are generated in a standard format that allows ready use with both specialized analysis tools like MapMan and PageMan and generic spreadsheet applications. To further improve user friendliness, Robin includes both integrated help and comprehensive external documentation. To demonstrate the statistical power and ease of use of the workflows in Robin, we present a case study in which we apply Robin to analyze a two-color microarray experiment comparing gene expression in tomato (Solanum lycopersicum) leaves, flowers, and roots.