Visualization of gene ontology and cluster analysis results
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
The purpose of the thesis is to develop a new visualization method for Gene Ontologiesand hierarchical clustering. These are both important tools in biology andmedicine to study high-throughput data such as transcriptomics and metabolomicsdata. Enrichment of ontology terms in the data is used to identify statistically overrepresentedontology terms, that give insight into relevant biological processes orfunctional modules. Hierarchical clustering is a standard method to analyze andvisualize data to nd relatively homogeneous clusters of experimental data points.Both methods support the analysis of the same data set, but are usually consideredindependently. However, often a combined view such as: visualizing a large data setin the context of an ontology under consideration of a clustering of the data.The result of the current work is a user-friendly program that combines twodi erent views for analysing Gene Ontology and Cluster simultaneously. To makeexplorations of such a big data possible we developed new visualization approach.
Place, publisher, year, edition, pages
2012. , 60 p.
Graph Visualization, Gene Ontology, Hierarchical Clustering, Mappings, Interaction
IdentifiersURN: urn:nbn:se:lnu:diva-21248OAI: oai:DiVA.org:lnu-21248DiVA: diva2:545893
Subject / course
Kerren, Andreas, Professor