COXPRESdb v8: an animal gene coexpression database navigating from a global view to detailed investigations.

Gene coexpression is synchronization of gene expression across many cellular and environmental conditions and is widely used to infer the biological function of genes. Gene coexpression information is complex, comprising a complete graph of all genes in the genome, and requires appropriate visualization and analysis tools. Since its initial release in 2007, the animal gene expression database COXPRESdb (https://coxpresdb.jp) has been continuously improved by adding new gene coexpression data and analysis tools. Here, we report COXPRESdb version 8, which has been enhanced with new features for an overview, summary, and individual examination of coexpression relationships: CoexMap to display coexpression on a genome scale, pathway enrichment analysis to summarize the function of coexpressed genes, and CoexPub to bridges coexpression and existing knowledge. COXPRESdb also facilitates downstream analyses such as interspecies comparisons by integrating RNAseq and microarray coexpression data in a union-type gene coexpression. COXPRESdb strongly support users with the new coexpression data and enhanced functionality.

ATTED-II v11: A Plant Gene Coexpression Database Using a Sample Balancing Technique by Subagging of Principal Components.

ATTED-II (https://atted.jp) is a gene coexpression database for nine plant species based on publicly available RNAseq and microarray data. One of the challenges in constructing condition-independent coexpression data based on publicly available gene expression data is managing the inherent sampling bias. Here, we report ATTED-II version 11, wherein we adopted a coexpression calculation methodology to balance the samples using principal component analysis and ensemble calculation. This approach has two advantages. First, omitting principal components with low contribution rates reduces the main contributors of noise. Second, balancing large differences in contribution rates enables considering various sample conditions entirely. In addition, based on RNAseq- and microarray-based coexpression data, we provide species-representative, integrated coexpression information to enhance the efficiency of interspecies comparison of the coexpression data. These coexpression data are provided as a standardized z-score to facilitate integrated analysis with different data sources. We believe that with these improvements, ATTED-II is more valuable and powerful for supporting interspecies comparative studies and integrated analyses using heterogeneous data.