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

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.

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Lohse-2010-Robin_ An Intuitive.pdf (Any fulltext), 743KB
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Lohse-2010-Robin_ An Intuitive.pdf
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 Creators:
Lohse, M.1, Author           
Nunes-Nesi, A.2, Author           
Krueger, P.3, Author           
Nagel, A.1, Author           
Hannemann, J.1, Author           
Giorgi, F. M.1, Author           
Childs, L.3, Author           
Osorio, S.2, Author           
Walther, D.3, Author           
Selbig, J.4, Author           
Sreenivasulu, N.5, Author
Stitt, M.6, Author           
Fernie, A. R.2, Author           
Usadel, B.1, Author           
Affiliations:
1Integrative Carbon Biology, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753329              
2Central Metabolism, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753339              
3BioinformaticsCIG, Infrastructure Groups and Service Units, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753303              
4BioinformaticsCRG, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753315              
5External Organizations, ou_persistent22              
6System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753327              

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Free keywords: graphical user-interface sucrose synthase arabidopsis-thaliana bioconductor package fruit-development sink strength gene growth tool patterns
 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.

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Language(s): eng - English
 Dates: 2010-04-152010
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: ISI:000278340200027
DOI: 10.1104/pp.109.152553
ISSN: 1532-2548 (Electronic)0032-0889 (Linking)
URI: ://000278340200027http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2879776/pdf/642.pdf?tool=pmcentrez
 Degree: -

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Title: Plant Physiology
  Other : Plant Physiol.
Source Genre: Journal
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Publ. Info: Bethesda, Md. : American Society of Plant Biologists
Pages: - Volume / Issue: 153 (2) Sequence Number: - Start / End Page: 642 - 651 Identifier: ISSN: 0032-0889
CoNE: https://pure.mpg.de/cone/journals/resource/991042744294438