STOP Using Just GO: A Multi-Ontology Enrichment Analysis Tool

Publication Date

Spring 2011

Degree Type

Master's Project

Degree Name

Master of Science (MS)


Computer Science


Enrichment analysis is a common technique used by biologists to reduce a large set of annotations to a smaller, more manageable set of significantly represented concepts. Currently, enrichment analysis is done primarily using Gene Ontology (GO). Because enrichment analysis is a reduction technique, the quality of the results depend entirely on the data used to create them. Although GO has been useful, there are entire domains of research that are not considered as part of that ontology (such as diseases or phenotypes). To solve this problem, we have created Statistical Tracking of Ontological Phrases (STOP), a multi- ontology automated enrichment analysis tool. STOP gathers text related to genes from the NCBI Entrez database and then automatically annotates it using the Stanford NCBO Annotator. STOP will perform enrichment analysis using any of the chosen ontologies. Users can select their own background dataset, or STOP will use a predefined background of the entire genome, or proteome for a given species. This project will show that automatic annotations are at least as good as manual annotations and multiple ontologies provide more useful information than single ontologies.

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