GOSim--an R-package for computation of information theoretic GO similarities between terms and gene products.

Holger Fröhlich,Tim Beißbarth,Annemarie Poustka,Nora Speer

doi:10.1186/1471-2105-8-166

Abstract

BackgroundWith the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the analysis of such data often there is the need to further explore the similarity of genes not only with respect to their expression, but also with respect to their functional annotation which can be obtained from Gene Ontology (GO).ResultsWe present the freely available software package GOSim, which allows to calculate the functional similarity of genes based on various information theoretic similarity concepts for GO terms. GOSim extends existing tools by providing additional lately developed functional similarity measures for genes. These can e.g. be used to cluster genes according to their biological function. Vice versa, they can also be used to evaluate the homogeneity of a given grouping of genes with respect to their GO annotation. GOSim hence provides the researcher with a flexible and powerful tool to combine knowledge stored in GO with experimental data. It can be seen as complementary to other tools that, for instance, search for significantly overrepresented GO terms within a given group of genes.ConclusionGOSim is implemented as a package for the statistical computing environment R and is distributed under GPL within the CRAN project.

Highlights

With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data
We present the freely available software package GOSim, which allows to calculate the functional similarity of genes based on various information theoretic similarity concepts for Gene Ontology (GO) terms
GOSim is implemented as a package for the statistical computing environment R and is distributed under GPL within the CRAN project

Summary

Introduction

With the increased availability of high throughput data, such as DNA microarray data, researchers are capable of producing large amounts of biological data. During the analysis of such data often there is the need to further explore the similarity of genes with respect to their expression, and with respect to their functional annotation which can be obtained from Gene Ontology (GO). Researchers often end up with long lists of interesting candidate genes that need further examination. At this point, a second step is almost always applied: biologists categorize these genes to known biological functions and try to combine experimental outcomes with biological knowledge. A second step is almost always applied: biologists categorize these genes to known biological functions and try to combine experimental outcomes with biological knowledge Such information is e.g. provided by Gene Ontology (GO). GO has become one of the most widespread systems for systematically annotating gene products within the bioinformatics community and is developed by the Gene Ontology Consortium [2] with the intention to describe gene products with a controlled (page number not for citation purposes)

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Conclusion