Abstract
This protocol describes how to build a gene network based on the graphical Gaussian model (GGM) from large scale microarray data. GGM uses partial correlation coefficient (pcor) to infer co-expression relationship between genes. Compared to the traditional Pearson’ correlation coefficient, partial correlation is a better measurement of direct dependency between genes. However, to calculate pcor requires a large number of observations (microarray slides) greatly exceeding the number of variables (genes). This protocol uses a regularized method to circumvent this obstacle, and is capable of building a network for ~20,000 genes from ~2,000 microarray slides. For more details, see Ma et al. (2007). For help regarding the script, please contact the author.
Data and Software
Equipment
Procedure
Acknowledgments
This protocol was developed by the author in Hans Bohnert’s lab, Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. The work was supported by grants from the National Science Foundation Plant Genome Project (DBI-0223905) and University of Illinois at Urbana-Champaign institutional grants.
References
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