Visual analysis of transcriptome data in the context of anatomical structures and biological networks
- 1Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben, Gatersleben, Germany
- 2Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany
- 3Clayton School of Information Technology, Monash University, Clayton, VIC, Australia
The complexity and temporal as well as spatial resolution of transcriptome datasets is constantly increasing due to extensive technological developments. Here we present methods for advanced visualization and intuitive exploration of transcriptomics data as necessary prerequisites in order to facilitate the gain of biological knowledge. Color-coding of structural images based on the expression level enables a fast visual data analysis in the background of the examined biological system. The network-based exploration of these visualizations allows for comparative analysis of genes with specific transcript patterns and supports the extraction of functional relationships even from large datasets. In order to illustrate the presented methods, the tool HIVE was applied for visualization and exploration of database-retrieved expression data for master regulators of Arabidopsis thaliana flower and seed development in the context of corresponding tissue-specific regulatory networks.
Keywords: omics data visualization, expression atlas, data integration, color-coding, biological network, systems biology graphical notation, visual analytics
Citation: Junker A, Rohn H and Schreiber F (2012) Visual analysis of transcriptome data in the context of anatomical structures and biological networks. Front. Plant Sci. 3:252. doi: 10.3389/fpls.2012.00252
Received: 01 August 2012; Accepted: 22 October 2012;
Published online: 15 November 2012.
Copyright: © 2012 Junker, Rohn and Schreiber. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
*Correspondence: Hendrik Rohn, Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben, Corrensstrasse 3, D-06466 Gatersleben, Germany. e-mail: firstname.lastname@example.org
†Astrid Junker and Hendrik Rohn have contributed equally to this work.