Semantic particularity measure for functional characterization of gene sets using gene ontology

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.

Figure 1. Representation of Exportin-5 orthologs annotations.

Common terms between species are displayed in blue. The terms annotating only the human ortholog are displayed in red. Part A of this figure displays the MF annotations of the human and rat orthologs of Exportin-5. Part B displays the MF annotations of the human and drosophila orthologs of Exportin-5. In this example, there is no rat nor drosophila-specific term. The semantic similarity values obtained in these cases do not reflect the difference of human particularity between each part.

Figure 2. Representation of ADH4 and SFA1 Saccharomyces cerevisiae annotations.

The particularity of 0.388 for SFA1 compared to ADH4 is explained notably by the term “nucleotide binding”, to which the closest ancestor with ADH4 annotations is at a distance of three edges. The other red terms are also responsible for this particularity.

Figure 3. MF annotations of two couples of human aquaporins.

Part A: AQP8 and AQP5 share most of their annotations. Part B: AQP6 and AQP3 share numerous molecular functions, but each gene also have particular functions.