School of Engineering, Pablo de Olavide University, Seville, Spain.
BMC Bioinformatics. 2011 Sep 1;12:360. doi: 10.1186/1471-2105-12-360.
The Gene Ontology (GO) provides a controlled vocabulary for describing the functions of genes and can be used to evaluate the functional coherence of gene sets. Many functional coherence measures consider each pair of gene functions in a set and produce an output based on all pairwise distances. A single gene can encode multiple proteins that may differ in function. For each functionality, other proteins that exhibit the same activity may also participate. Therefore, an identification of the most common function for all of the genes involved in a biological process is important in evaluating the functional similarity of groups of genes and a quantification of functional coherence can helps to clarify the role of a group of genes working together.
To implement this approach to functional assessment, we present GFD (GO-based Functional Dissimilarity), a novel dissimilarity measure for evaluating groups of genes based on the most relevant functions of the whole set. The measure assigns a numerical value to the gene set for each of the three GO sub-ontologies.
Results show that GFD performs robustly when applied to gene set of known functionality (extracted from KEGG). It performs particularly well on randomly generated gene sets. An ROC analysis reveals that the performance of GFD in evaluating the functional dissimilarity of gene sets is very satisfactory. A comparative analysis against other functional measures, such as GS2 and those presented by Resnik and Wang, also demonstrates the robustness of GFD.
基因本体论 (GO) 提供了一个描述基因功能的受控词汇表，可用于评估基因集的功能一致性。许多功能一致性度量考虑了一个集合中的每对基因功能，并根据所有的成对距离生成输出。单个基因可以编码多种功能不同的蛋白质。对于每种功能，其他表现出相同活性的蛋白质也可能参与其中。因此，确定参与生物过程的所有基因的最常见功能对于评估基因集的功能相似性以及量化功能一致性非常重要，因为这有助于阐明一组共同发挥作用的基因的作用。
为了实现这种功能评估方法，我们提出了 GFD（基于 GO 的功能差异），这是一种新的差异度量方法，用于根据整个集合的最相关功能评估基因集。该度量方法为三个 GO 子本体中的每一个分配一个数值给基因集。
结果表明，GFD 在应用于具有已知功能的基因集（从 KEGG 中提取）时表现稳健。它在随机生成的基因集上表现尤其出色。ROC 分析表明，GFD 在评估基因集功能差异方面的性能非常令人满意。与其他功能度量方法（如 GS2 和 Resnik 和 Wang 提出的方法）的比较分析也证明了 GFD 的稳健性。
