Comparative study of RNA-seq- and microarray-derived coexpression networks in Arabidopsis thaliana

Motivation: Coexpression networks are data-derived representations of genes behaving in a similar way across tissues and experimental conditions. They have been used for hypothesis generation and guilt-by-association approaches for inferring functions of previously unknown genes. So far, the main platform for expression data has been DNA microarrays; however, the recent development of RNA-seq allows for higher accuracy and coverage of transcript popu-lations. It is therefore important to assess the potential for biological investigation of coexpression networks derived from this novel tech-nique in a condition-independent dataset. Results: We collected 65 publicly available Illumina RNA-seq high quality Arabidopsis thaliana samples and generated Pearson correl-ation coexpression networks. These networks were then compared with those derived from analogous microarray data. We show ho