Enabling data analysis on high-throughput data in large data depository using web-based analysis platform - A case study on integrating QUEST with GenePattern in epigenetics research

Terry Camerlengo, Hatice Gulcin Ozer, Pearlly Yan, Jeffrey Parvin, Tim Huang, Kun Huang, Mingxiang Teng, Lang Li, Yunlong Liu, Francisco Perez, Tahsin Kurc

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Enabling data analysis in large data depositories for high throughput experimental data such as gene microarrays and ChIP-seq is challenging. In this paper, we discuss three methods for integrating QUEST, a data depository for epigenetic experiments, with a web-based data analysis platform GenePattern. These methods are universal and can serve as an exemplary implementation resolving the dilemma facing many similar database systems in integrating data analysis tools.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
Pages392-395
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009 - Washington, D.C., United States
Duration: Nov 1 2009Nov 4 2009

Publication series

Name2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009

Other

Other2009 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2009
CountryUnited States
CityWashington, D.C.
Period11/1/0911/4/09

Keywords

  • ChIP-seq
  • GenePattern
  • High-throughput database

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Biomedical Engineering
  • Health Informatics

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