| The use of open source bioinformatics tools to dissect transcriptomic data. | |
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MedLine Citation:
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PMID: 22183662 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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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. |
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Authors:
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Benjamin M Nitsche; Arthur F J Ram; Vera Meyer |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Methods in molecular biology (Clifton, N.J.) Volume: 835 ISSN: 1940-6029 ISO Abbreviation: Methods Mol. Biol. Publication Date: 2012 |
Date Detail:
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Created Date: 2011-12-20 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9214969 Medline TA: Methods Mol Biol Country: United States |
Other Details:
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Languages: eng Pagination: 311-31 Citation Subset: IM |
Affiliation:
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Department Molecular Microbiology and Biotechnology, Institute of Biology Leiden, Leiden University, Leiden, The Netherlands. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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