关于研究的研究:dbGaP研究相关元数据的探索

Karen Truong, Mike Conway
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引用次数: 1

摘要

基因型和表型数据库(dbGaP)是由国家心肺和血液研究所(NHLBI)开发的,用于存档全基因组关联研究(GWAS)数据。截至2012年7月17日,dbGaP共收录305项顶级研究。每个研究的元数据(可从dbGaP网站获得)被组织成不同的部分,包括研究描述、纳入/排除标准、授权访问请求策略、MeSH术语、PubMed标识符、研究历史以及主要和共同研究者的姓名。我们在此将dbGaP元数据的显著特征制成表格,作为表现型发现者(Phenotype Discoverer, PhD)项目的一部分。表现型发现者(Phenotype Discoverer, PhD)项目是加州大学圣地亚哥分校生物医学信息部的一个研究项目,旨在通过将表现型与标准信息模型相结合,增强当前dbGaP网站的“可搜索性”。特别是,我们对使用提取的元数据PubMed标识符、主要研究者姓名、相关期刊名称等作为统计文本的输入感兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on Studies: Exploring the Metadata Associated with dbGaP Studies
The database of Genotypes and Phenotypes (dbGaP) was developed by the National Heart Lung, and Blood Institute (NHLBI) to archive genome-wide association studies (GWAS) data. As of July 17th 2012, dbGaP contained 305 top-level studies. The metadata for each study (available from the dbGaP website) are organized into distinct sections, including a study description, inclusion/exclusion criteria, policies for authorized access requests, MeSH terms, PubMed identifiers, study histories, and the names of principal and co-investigators. We here tabulate the salient characteristics of dbGaP metadata as part of the Phenotype Discoverer (PhD) project, a research project at the University of California San Diego Division of Biomedical Informatics which aims to enhance the "searchability" of the current dbGaP website through the alignment of phenotypes to a standard information model. In particular, we are interested in using the extracted metadata PubMed identifiers, principal investigator names, associated journal names, etc. as input to a statistical text.
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