PhenoMiner: from text to a database of phenotypes associated with OMIM diseases
PhenoMiner: from text to a database of phenotypes associated with OMIM diseases
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DOI：
10.1093/database/bav104
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发表时间：
2015-10-27
影响因子：
5.8
通讯作者：
Rebholz-Schuhmann, Dietrich
中科院分区：
文献类型：
--
作者：
Collier, Nigel;Groza, Tudor;Rebholz-Schuhmann, Dietrich
对实验文献中报告的科学和临床表型的分析已经人工策划，以建立高质量的数据库，如在线孟德尔遗传人类（OMIM）。然而，表型描述的识别和协调与人类表达能力的多样性相矛盾。我们介绍了一种新的自动提取方法称为PhenoMiner，充分利用解析和概念分析。然后使用先验关联挖掘来确定与人类疾病的关系。我们将PhenoMiner应用于BMC开放获取集合，并确定了13636个表型候选者。我们确定了28155个表型-疾病假说，涵盖4898个表型和1659个孟德尔疾病。分析显示：（i）提取的术语的语义分布与链接的本体;（ii）术语重叠与人类表型本体（HP）的比较;（iii）在OMIM和文献中对表型-病症对的适度支持;（iv）表型-病症对与使用PhenoDigm的已知疾病-基因对的强关联。PhenoMiner表型（S1），表型-疾病关联（S2），关联过滤的链接数据（S3）和用户数据库文档（S5）的完整列表可作为补充数据提供，并可在Creative Commons Attribution 4.0许可下在http://github.com/nhcollier/PhenoMiner下载。
Analysis of scientific and clinical phenotypes reported in the experimental literature has been curated manually to build high-quality databases such as the Online Mendelian Inheritance in Man (OMIM). However, the identification and harmonization of phenotype descriptions struggles with the diversity of human expressivity. We introduce a novel automated extraction approach called PhenoMiner that exploits full parsing and conceptual analysis. Apriori association mining is then used to identify relationships to human diseases. We applied PhenoMiner to the BMC open access collection and identified 13 636 phenotype candidates. We identified 28 155 phenotype-disorder hypotheses covering 4898 phenotypes and 1659 Mendelian disorders. Analysis showed: (i) the semantic distribution of the extracted terms against linked ontologies; (ii) a comparison of term overlap with the Human Phenotype Ontology (HP); (iii) moderate support for phenotype-disorder pairs in both OMIM and the literature; (iv) strong associations of phenotype-disorder pairs to known disease-genes pairs using PhenoDigm. The full list of PhenoMiner phenotypes (S1), phenotype-disorder associations (S2), association-filtered linked data (S3) and user database documentation (S5) is available as supplementary data and can be downloaded at http://github.com/nhcollier/PhenoMiner under a Creative Commons Attribution 4.0 license.