Bioinformatics Advance Access originally published online on July 29, 2004
Bioinformatics 2004 20(18):3565-3574; doi:10.1093/bioinformatics/bth445
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Bioinformatics vol. 20 issue 18 © Oxford University Press 2004; all rights reserved.
Discovery of meaningful associations in genomic data using partial correlation coefficients
Virginia Polytechnic Institute and State University, Virginia Bioinformatics Institute, 1880 Pratt Drive, Blacksburg, Virginia, 24061 USA
Received on June 2, 2004; revised on July 15, 2004; accepted on July 24, 2004
Advance Access Publication July 29, 2004
Motivation: A major challenge of systems biology is to infer biochemical interactions from large-scale observations, such as transcriptomics, proteomics and metabolomics. We propose to use a partial correlation analysis to construct approximate Undirected Dependency Graphs from such large-scale biochemical data. This approach enables a distinction between direct and indirect interactions of biochemical compounds, thereby inferring the underlying network topology.
Results: The method is first thoroughly evaluated with a large set of simulated data. Results indicate that the approach has good statistical power and a low False Discovery Rate even in the presence of noise in the data. We then applied the method to an existing data set of yeast gene expression. Several small gene networks were inferred and found to contain genes known to be collectively involved in particular biochemical processes. In some of these networks there are also uncharacterized ORFs present, which lead to hypotheses about their functions.
Availability: Programs running in MS-Windows and Linux for applying zeroth, first, second and third order partial correlation analysis can be downloaded at: http://mendes.vbi.vt.edu/tiki-index.php?page=Software
Supplementary information: Supplementary information can be found at: URL to be decided
Contact: alf{at}vbi.vt.edu
* To whom correspondence should be addressed.
Present address: GlaxoSmithKline, Five Moore Drive, Research Triangle Park, North Carolina, 27709
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