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Theresa Harbig, Kay Nieselt (Institute for Bioinformatics and Medical Informatics, University of Tübingen, Germany)
Analysis pipelines for high-throughput transcriptome data often produce long lists of differentially expressed genes. For functional analysis, these lists can be analyzed using Gene Ontology (GO) enrichment analysis. The lists produced are often long, redundant, and hard to compare. GO-Compass takes multiple lists of genes as an input and computes GO term enrichment, resulting in lists of GO terms with associated p-values. The GO terms are clustered hierarchically based on their dispensability which is derived from their semantic similarity. Based on the clustering users can interactively compare GO enrichment at different conditions in a visualization dashboard. By cutting the hierarchical clustering at a specific dispensability, flat clusters are created, which are visualized as treemaps, where the size of the rectangles corresponds to the negative logarithm of the p-values of the GO terms. The dashboard makes use of several visualization techniques such as linked highlighting, animated transitions of the treemaps, and overview plots. We believe that GO-Compass provides a novel way to compare long lists of genes, which is independent of the species or the source of the data.