From disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose ontology for the test of gene-ontology associations.
From disease ontology to disease-ontology lite: statistical methods to adapt a general-purpose ontology for the test of gene-ontology associations.
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DOI：
10.1093/bioinformatics/btp193
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发表时间：
2009-06-15
期刊：
影响因子：
--
通讯作者：
Lin SM
中科院分区：
文献类型：
--
作者：
Du P;Feng G;Flatow J;Song J;Holko M;Kibbe WA;Lin SM
主观方法已被报道为适应特定应用的通用本体。例如，基因本体（GO） Slim是由GO创建的，用于生成高度聚合的人类基因组注释报告。我们提出了统计方法，以适应一般目的，OBO铸造疾病本体（DO），以识别基因-疾病关联。因此，我们需要一个源自相关基因的疾病类别的简化定义。在假设具有相似相关基因的DO术语密切相关的基础上，我们根据基因-DO -DO图谱的相似性对DO术语进行了分组。定义了两种类型的二进制距离度量来度量DO项之间的总体和子集相似性。然后应用紧凑可扩展模糊聚类方法对相似DO项进行分组。为了减少错误聚类，还使用DO术语之间的语义相似性来约束聚类结果。因此，DO项被聚合，多余的DO项被大部分删除。使用这些方法，我们从DO中构建了一个简化的词汇表，称为疾病本体Lite （DOLite）。我们证明，在基因-疾病关联测试中，DOLite的结果比DO更具可解释性。生成的DOLite已用于功能疾病本体（FunDO） Web应用程序http://www.projects.bioinformatics.northwestern.edu/fundo。联系人:s-lin2@northwestern.edu
Subjective methods have been reported to adapt a general-purpose ontology for a specific application. For example, Gene Ontology (GO) Slim was created from GO to generate a highly aggregated report of the human-genome annotation. We propose statistical methods to adapt the general purpose, OBO Foundry Disease Ontology (DO) for the identification of gene-disease associations. Thus, we need a simplified definition of disease categories derived from implicated genes. On the basis of the assumption that the DO terms having similar associated genes are closely related, we group the DO terms based on the similarity of gene-to-DO mapping profiles. Two types of binary distance metrics are defined to measure the overall and subset similarity between DO terms. A compactness-scalable fuzzy clustering method is then applied to group similar DO terms. To reduce false clustering, the semantic similarities between DO terms are also used to constrain clustering results. As such, the DO terms are aggregated and the redundant DO terms are largely removed. Using these methods, we constructed a simplified vocabulary list from the DO called Disease Ontology Lite (DOLite). We demonstrated that DOLite results in more interpretable results than DO for gene-disease association tests. The resultant DOLite has been used in the Functional Disease Ontology (FunDO) Web application at http://www.projects.bioinformatics.northwestern.edu/fundo. Contact: s-lin2@northwestern.edu
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