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Semantic Particularity Measure for Functional Characterization of Gene Sets Using Gene Ontology

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  • Charles Bettembourg
  • Christian Diot
  • Olivier Dameron

Abstract

Background: Genetic and genomic data analyses are outputting large sets of genes. Functional comparison of these gene sets is a key part of the analysis, as it identifies their shared functions, and the functions that distinguish each set. The Gene Ontology (GO) initiative provides a unified reference for analyzing the genes molecular functions, biological processes and cellular components. Numerous semantic similarity measures have been developed to systematically quantify the weight of the GO terms shared by two genes. We studied how gene set comparisons can be improved by considering gene set particularity in addition to gene set similarity. Results: We propose a new approach to compute gene set particularities based on the information conveyed by GO terms. A GO term informativeness can be computed using either its information content based on the term frequency in a corpus, or a function of the term's distance to the root. We defined the semantic particularity of a set of GO terms Sg1 compared to another set of GO terms Sg2. We combined our particularity measure with a similarity measure to compare gene sets. We demonstrated that the combination of semantic similarity and semantic particularity measures was able to identify genes with particular functions from among similar genes. This differentiation was not recognized using only a semantic similarity measure. Conclusion: Semantic particularity should be used in conjunction with semantic similarity to perform functional analysis of GO-annotated gene sets. The principle is generalizable to other ontologies.

Suggested Citation

  • Charles Bettembourg & Christian Diot & Olivier Dameron, 2014. "Semantic Particularity Measure for Functional Characterization of Gene Sets Using Gene Ontology," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
  • Handle: RePEc:plo:pone00:0086525
    DOI: 10.1371/journal.pone.0086525
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    References listed on IDEAS

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    1. Catia Pesquita & Daniel Faria & André O Falcão & Phillip Lord & Francisco M Couto, 2009. "Semantic Similarity in Biomedical Ontologies," PLOS Computational Biology, Public Library of Science, vol. 5(7), pages 1-12, July.
    2. Billy Chang & Rafal Kustra & Weidong Tian, 2013. "Functional-Network-Based Gene Set Analysis Using Gene-Ontology," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-13, February.
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    1. Charles Bettembourg & Christian Diot & Olivier Dameron, 2015. "Optimal Threshold Determination for Interpreting Semantic Similarity and Particularity: Application to the Comparison of Gene Sets and Metabolic Pathways Using GO and ChEBI," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-30, July.

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