Assessing Microarray Quality

• Activity Number: 507
• Type: Contributed
• Date/Time: Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
• Sponsor: Biometrics Section
• Author(s): Matthew Nicholson McCall*+ and Peter Murakami and Rafael Irizarry
• Companies: University of Rochester Medical Center and The Johns Hopkins University and The Johns Hopkins University
• Keywords: microarray ; quality ; single-array ; Affymetrix

Abstract

For microarrays to become generally accepted as a reliable technology, statistical methods for assessing quality will be an indispensable component; however, there remains a lack of consensus in both defining and measuring microarray quality. We provide a precise definition of microarray quality and review existing quality metrics in light of this definition. The best-performing quality metrics require multiple arrays to be assessed simultaneously. While such metrics are adequate for bench science, as microarrays begin to be used in clinical settings, single-array metrics will be indispensable. To this end, we define a single-array version of a popular multi-array quality metric and show that this metric is comparable to the best multi-array metrics. Finally, we use this new quality metric to assess the quality of over 22,000 publicly available microarrays. We find that approximately 10% of these arrays are of poor quality. Moreover, the quality of microarray measurements varies greatly from hybridization to hybridization, study to study, and lab to lab, with some experiments producing unusable data.