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  • 标题:Precision annotation of digital samples in NCBIs gene expression omnibus
  • 本地全文:下载
  • 作者:Dexter Hadley ; James Pan ; Osama El-Sayed
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2017
  • 卷号:4
  • DOI:10.1038/sdata.2017.125
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要:The Gene Expression Omnibus (GEO) contains more than two million digital samples from functional genomics experiments amassed over almost two decades. However, individual sample meta-data remains poorly described by unstructured free text attributes preventing its largescale reanalysis. We introduce the Search Tag Analyze Resource for GEO as a web application (http://STARGEO.org) to curate better annotations of sample phenotypes uniformly across different studies, and to use these sample annotations to define robust genomic signatures of disease pathology by meta-analysis. In this paper, we target a small group of biomedical graduate students to show rapid crowd-curation of precise sample annotations across all phenotypes, and we demonstrate the biological validity of these crowd-curated annotations for breast cancer. STARGEO.org makes GEO data findable, accessible, interoperable and reusable (i.e., FAIR) to ultimately facilitate knowledge discovery. Our work demonstrates the utility of crowd-curation and interpretation of open 鈥榖ig data鈥?under FAIR principles as a first step towards realizing an ideal paradigm of precision medicine.
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