PLANEX: The plant co-expression database obtained from GEO NCBI.

  The PLANt co-EXpression database (PLANEX) is a new internet-based database for plant gene analysis. PLANEX is based on publicly available GeneChip data obtained from Gene Expression Omnibus (GEO) of the National Center for Biotechnology Information (NCBI). PLANEX is a genome-wide co-expression database and can be used for broad experimental designs, such as characterization of genes for functional identification and analysis of their dependency among genes. A database for co-expressed genes can provide functional identification from a wide variety of experimental designs. Other gene co-expression databases have been developed by other researchers, but the information for plant genes is rather limited. Therefore, we constructed PLANEX as a co-expressed gene list and functional annotation for Arabidopsis thaliana, Glycine max, Hordeum vulgare, Oryza sativa, Solanum lycopersicum, Triticum aestivum, Vitis vinifera and Zea mays. PLANEX shows Pearson’s correlation coefficients (PCCs; r-value) that distribute from a gene of interest for a given microarray platform set corresponding to a particular organism. To support PCCs, PLANEX performs an enrichment test of Gene Ontology terms and Cohen’s Kappa value to compare functional similarity for all genes in the co-expression database. PLANEX draws a cluster network with co-expressed genes, which is estimated using the k-mean method. To contstruct PLANEX, a variety of datasets were interpreted by the IBM supercomputer Advanced Interactive eXecutive (AIX) in a supercomputing center. PLANEX provides a correlation database, a cluster network and an interpretation of enrichment test results for eight species. A typical co-expressed gene can generate many lists of co-expression data that contain hundreds of genes of interest for enrichment analysis. Also, co-expressed genes can be identified and cataloged in terms of comparative genomics by using the ‘Co-expression gene compare’ feature. This analysis will help interpret experimental data and determine whether there is a common term to those genes.