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. 2007 Jan;35(Database issue):D766-70.
doi: 10.1093/nar/gkl1019. Epub 2006 Dec 20.

The Stanford Microarray Database: implementation of new analysis tools and open source release of software

Janos Demeter  1 , Catherine Beauheim, Jeremy Gollub, Tina Hernandez-Boussard, Heng Jin, Donald Maier, John C Matese, Michael Nitzberg, Farrell Wymore, Zachariah K Zachariah, Patrick O Brown, Gavin Sherlock, Catherine A Ball
Affiliations

The Stanford Microarray Database: implementation of new analysis tools and open source release of software

Janos Demeter et al. Nucleic Acids Res. 2007 Jan.

Abstract

The Stanford Microarray Database (SMD; http://smd.stanford.edu/) is a research tool and archive that allows hundreds of researchers worldwide to store, annotate, analyze and share data generated by microarray technology. SMD supports most major microarray platforms, and is MIAME-supportive and can export or import MAGE-ML. The primary mission of SMD is to be a research tool that supports researchers from the point of data generation to data publication and dissemination, but it also provides unrestricted access to analysis tools and public data from 300 publications. In addition to supporting ongoing research, SMD makes its source code fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD. In this article, we describe several data analysis tools implemented in SMD and we discuss features of our software release.

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Figures

Figure 1
Figure 1
Result of an SVD analysis in SMD. (a) Raster display of the eigengenes (left panel) and bar chart display of the probabilities of eigenexpression (right panel) of a sample dataset. (b) Plot showing the behavior of the top four eigengenes. (c) Projection of genes within an eigengene. This image shows how all genes in a dataset are projected onto a given eigengene. This is one way to determine those genes whose expression is contributed to by an eigengene.
Figure 2
Figure 2
GO TermFinder analysis in SMD. (a) User interface to upload the required files (list of genes that make up an interesting cluster and background file from which the cluster was derived) and make selections of gene identifiers used in the uploaded files, the desired sub-ontology to use and significance value and parameter to use. (b) The graphical display of a positive result output from GO TermFinder. The graph shows the genes of the input cluster in the context of the relevant part of Gene Ontology. The GO terms that are found to have significant enrichment are colored according to the significance level.
See this image and copyright information in PMC

References

    1. Ball C.A., Awad I.A., Demeter J., Gollub J., Hebert J.M., Hernandez-Boussard T., Jin H., Matese J.C., Nitzberg M., Wymore F., et al. The Stanford Microarray Database accommodates additional microarray platforms and data formats. Nucleic Acids Res. 2005;33:D580–D582. - PMC - PubMed
    1. Ball C.A., Sherlock G., Parkinson H., Rocca-Sera P., Brooksbank C., Causton H.C., Cavalieri D., Gaasterland T., Hingamp P., Holstege F., et al. Standards for microarray data. Science. 2002;298:539. - PubMed
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    1. Spellman P.T., Miller M., Stewart J., Troup C., Sarkans U., Chervitz S., Bernhart D., Sherlock G., Ball C., Lepage M., et al. Design and implementation of microarray gene expression markup language (MAGE-ML) Genome Biol. 2002;3:RESEARCH0046. - PMC - PubMed
    1. Brazma A., Parkinson H., Sarkans U., Shojatalab M., Vilo J., Abeygunawardena N., Holloway E., Kapushesky M., Kemmeren P., Lara G.G., et al. ArrayExpress—a public repository for microarray gene expression data at the EBI. Nucleic Acids Res. 2003;31:68–71. - PMC - PubMed

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