MarcCarlson

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Supplementary Material for the Weighted Gene Co-expression Network Application:

“Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks”, Marc RJ Carlson, Bin Zhang, Zixing Fang, Paul S Mischel, Steve Horvath, Stanley F Nelson, BMC Genomics 2006, 7:40 (3 March 2006).
http://www.biomedcentral.com/1471-2164/7/40/

Email Adrresses:                                                              MRJCarlson@mednet.ucla.edu
                                                                                               binzhang@mednet.ucla.edu
                                                                                               fang@CancerPreventionInstitute.org
                                                                                               PMischel@mednet.ucla.edu
                                                                                               snelson@ucla.edu
Statistical correspondence:                                          shorvath@mednet.ucla.edu

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ABSTRACT

Background

        Genes and proteins are organized into functional modular networks in which the network context of a gene or protein has implications for cellular function. Highly connected hub proteins, largely responsible for maintaining network connectivity, have been found to be much more likely to be essential for survival.

Results

        Here we investigate the relationship between connectivity and essentiality as well as between connectivity and gene sequence conservation in multiple independent data sets. We explore the modular structure of weighted co-expression networks in yeast and show that fundamental modules are preserved across multiple data sets. We also demonstrate how the reliability of a predicted modules construction can be tested by observing whether the local network properties retain the predictive power for determining the relative importance of a gene.

Conclusion

        Application of these techniques allows a finer scale prediction of relative gene importance for a particular process within a group of similarly expressed genes.

CONTENTS

                                                             * Datasets (zipped)         * R-code           * Functions

Other material regarding weighted gene co-expression network analysis

             Weighted Gene Co-Expression Network Page

             The weighted gene co-expression network analysis method is described in Theory Paper 1: Zhang and Horvath (2005)

             For a more mathematical description of weighted gene co-expression networks consider Theory Papers: Dong and Horvath (2007, 2008)

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2008-11-12

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Please send your suggestions and comments to: shorvath@mednet.ucla.edu