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 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.