BioDQ: data quality estimation and management for genomics databases

Authors:
Alexandra Martinez;Joachim Hammer;Sanjay Ranka
Affiliations:
Microsoft Corp., Redmond, WA and Dept of Computer & Information Science & Engineering, University of Florida, Gainesville, FL;Dept of Computer & Information Science & Engineering, University of Florida, Gainesville, FL;Dept of Computer & Information Science & Engineering, University of Florida, Gainesville, FL
Venue:
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Year:
2008

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Abstract

We present BIODQ, a model for estimating and managing the qualityof biological data in genomics repositories. BIODQ uses our Quality EstimationModel (QEM) which has been implemented as part of the Quality ManagementArchitecture (QMA). The QEM consists of a set of quality dimensions and theirquantitative measures. The QMA combines a series of software componentsthat enable the integration of QEM with existing genomics repositories. Thebasis of our experimental evaluation is a research study conducted amongbiologists. Evaluation results show that the QEM dimensions and estimationsare biologically-relevant and useful for discriminating high quality from lowquality data. The most relevant capabilities of the QMA are also presented.