Gene Coexpression Analysis

Gene expression data from fifteen different rice gene expression experiments have been analyzed to identify modules of genes with highly correlated expression patterns. Gene coexpression modules were identified using the WGCNA method (Zhang et al 2005). In this analysis, the data from the individual experiments were analyzed separately. The total number of genes analzyed in each experiment was reduced to remove unexpressed genes, constitutive genes and genes with slight expression variation using a coefficient of variation filter. The gene report pages for genes that were included in these analyses have a Gene Associations section that shows a trend plot of the normalized gene expression values for each gene from a single module.

Details about each experiment and the gene modules identified within each can be found on the experiment report pages:

Four search tools have been developed to help researchers explore these gene coexpression results.

• Create Gene Expression Plots
• Gene Correlation Search Within a Module
• Gene Correlation Search Within an Experiment
• Gene Correlation Search Within All Experiments

The gene coexpression analyses were performed with release 6.1 gene models. See the FAQ page for more information.

Files related to these analyses can be downloaded here.

A manuscript describing these analyses is available: Childs KL, Davidson RM, Buell CR (2011) Gene Coexpression Network Analysis as a Source of Functional Annotation for Rice Genes. PLoS ONE 6(7): e22196

This work is supported by grants (DBI-0321538/DBI-0834043) from the National Science Foundation and funds from the Georgia Research Alliance, Georgia Seed Development, and University of Georgia.