A Randomized MicroRNA Microarray Study and Its Evaluation of Normalization

• Activity Number: 649
• Type: Contributed
• Date/Time: Thursday, August 8, 2013 : 8:30 AM to 10:20 AM
• Sponsor: ENAR
• Author(s): Li-Xuan Qin*+ and Qin Zhou
• Companies: Memorial Sloan-Kettering Cancer Center and Memorial Sloan Kettering Cancer Center
• Keywords: microarray ; microRNA ; normalization ; randomization ; cancer ; genomics

Abstract

MicroRNA microarrays possess a number of unique data features that challenge the assumption key to existing normalization methods. They need to be re-assessed using genuine benchmark datasets that realistically represent data characteristics of microRNA arrays. We developed a randomized benchmark dataset free of confounding batch effects comparing endometrial and ovarian tumors. The benchmark dataset was assessed for differential expression and treated as the gold standard. We used the same tumor samples to generate a test dataset allowing for batch effects. After normalization, the test dataset was assessed for differential expression and compared with the gold standard. We observed moderate and asymmetric differential expression between endometrial and ovarian tumors in the benchmark dataset. Among the 3,523 microRNA markers on Agilent arrays, 351 (10%) were differentially expressed at a p-value cutoff of 0.01, with 210 over-expressed in ovarian tumors. Array effects were observed in the test data and resulted in a true positive rate (TPR) of 53% and a false discovery rate (FDR) of 90%. Normalization improved the TPR significantly but still possesses a FDR as high as 55%.