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

Author

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

Author_Institution

Ohio State Univ., Columbus, OH, USA

fYear

2009

fDate

1-4 Nov. 2009

Firstpage

392

Lastpage

395

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.

Keywords

genetics; medical information systems; molecular biophysics; GenePattern; QUEST; data analysis tools; database systems; epigenetics research; gene microarrays; high-throughput data; large data depository; web-based analysis platform; Bioinformatics; Biological processes; Data analysis; Database systems; Gene expression; Genomics; Java; Pipelines; Throughput; USA Councils; ChIP-seq; GenePattern; high-throughput database;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine, 2009. BIBM '09. IEEE International Conference on

Conference_Location

Washington, DC

Print_ISBN

978-0-7695-3885-3

Type

conf

DOI

10.1109/BIBM.2009.84

Filename

5341750