Data Quality Metrics for Genome Wide Association Studies

Genome Wide Association Studies (GWAS) are developed to find direct or indirect relations from given genomic configurations to physical characteristics or specific diseases. In order to build new GWAS, avoiding the complexities of field based studies, a statistical technique called meta-analysis can...

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Bibliographic Details
Main Authors: Etcheverry, Lorena, Marotta, Adriana, Ruggia, Raul
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Bioinformatics
Biological system modeling
component
Data models
data quality
Genomics
GWAS
meta-analysis
Online Access:Request full text
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Summary:Genome Wide Association Studies (GWAS) are developed to find direct or indirect relations from given genomic configurations to physical characteristics or specific diseases. In order to build new GWAS, avoiding the complexities of field based studies, a statistical technique called meta-analysis can be used. Bad or unknown data quality has been largely identified as a major problem in meta-analysis since it generates lack of confidence and inhibits its exploitation. This paper addresses GWAS data quality issues and presents a domain specific model for data quality assessment, which has been developed taking into account meta-analysis requirements.
ISSN:1529-4188
2378-3915
DOI:10.1109/DEXA.2010.40