Data Harmonization for a Molecularly Driven Health System

• Jerry Ssu-Hsien Lee ^[1] ; Warren Alden Kibbe ^[2] ; Robert L. Grossman ^[3]
  1. [1] University of Southern California

     University of Southern California

     Estados Unidos

     
  2. [2] Duke University

     Duke University

     Township of Durham, Estados Unidos

     
  3. [3] University of Chicago

     University of Chicago

     City of Chicago, Estados Unidos

     

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• Localización: Cell, ISSN 0092-8674, Vol. 174, Nº. 5, 2018, págs. 1045-1048
• Idioma: inglés
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• Resumen

  • Data commons have emerged as the best current method for enabling data aggregation across multiple projects and multiple data sources. Good data harmonization techniques are critical to maintain quality of data within a data commons, as well as to allow future meta-analysis across different data commons. We present some of the current best practices for data harmonization.