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. 2008 Jan;36(Database issue):D866-70.
doi: 10.1093/nar/gkm815. Epub 2007 Oct 11.

Many Microbe Microarrays Database: uniformly normalized Affymetrix compendia with structured experimental metadata

Jeremiah J Faith  1 , Michael E Driscoll, Vincent A Fusaro, Elissa J Cosgrove, Boris Hayete, Frank S Juhn, Stephen J Schneider, Timothy S Gardner
Affiliations

Many Microbe Microarrays Database: uniformly normalized Affymetrix compendia with structured experimental metadata

Jeremiah J Faith et al. Nucleic Acids Res. 2008 Jan.

Abstract

Many Microbe Microarrays Database (M3D) is designed to facilitate the analysis and visualization of expression data in compendia compiled from multiple laboratories. M3D contains over a thousand Affymetrix microarrays for Escherichia coli, Saccharomyces cerevisiae and Shewanella oneidensis. The expression data is uniformly normalized to make the data generated by different laboratories and researchers more comparable. To facilitate computational analyses, M3D provides raw data (CEL file) and normalized data downloads of each compendium. In addition, web-based construction, visualization and download of custom datasets are provided to facilitate efficient interrogation of the compendium for more focused analyses. The experimental condition metadata in M3D is human curated with each chemical and growth attribute stored as a structured and computable set of experimental features with consistent naming conventions and units. All versions of the normalized compendia constructed for each species are maintained and accessible in perpetuity to facilitate the future interpretation and comparison of results published on M3D data. M3D is accessible at http://m3d.bu.edu/.

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Figures

Figure 1.
Figure 1.
All of the available E. coli Affymetrix Antisense2 expression data for the transcription factor lexA and its known target recA were downloaded from NCBI GEO Profiles (A) and from M3D compendium E_coli_v3_Build_1 (B and C). NCBI GEO Profile data is derived from NCBI GEO DataSets that contain only a subset of the data in GEO, therefore many more samples were available for plotting from M3D (445) than from GEO (85). The correlation between lexA and its known target was higher when the raw data was uniformly normalized with RMA (C) rather than normalizing each microarray individually with MAS5 (A and B).
Figure 2.
Figure 2.
Custom datasets constructed on M3D can be visualized with scatterplots (A), histograms of individual genes (B), heatplots (C), histograms of collections of genes (D) and in their genome context using a genome browser (E).
See this image and copyright information in PMC

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