Precision Profiling and Components of Variability Analysis for Affymetrix Microarray Assays Run in a Clinical Context

• Published in: The Journal of molecular diagnostics : JMD Vol. 7; no. 3; pp. 404 - 412
• Main Authors: Daly, Thomas M., Dumaual, Carmen M., Dotson, Crystal A., Farmen, Mark W., Kadam, Sunil K., Hockett, Richard D.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.08.2005; ASIP; American Society for Investigative Pathology
• Subjects: DNA, Complementary - standards; Female; Gene Expression Profiling; Humans; Leiomyosarcoma - diagnosis; Leiomyosarcoma - genetics; Leukemia - diagnosis; Leukemia - genetics; Oligonucleotide Array Sequence Analysis - standards; Oligonucleotides - standards; Quality Control; Reference Standards; Regular; Reproducibility of Results; RNA, Complementary - standards; Sensitivity and Specificity; Uterine Neoplasms - diagnosis; Uterine Neoplasms - genetics
• ISSN: 1525-1578; 1943-7811
• DOI: 10.1016/S1525-1578(10)60570-3

Although gene expression profiling using microarray technology is widely used in research environments, adoption of microarray testing in clinical laboratories is currently limited. In an attempt to determine how such assays would perform in a clinical laboratory, we evaluated the analytical variability of Affymetrix microarray probesets using two generations of human Affymetrix chips (U95Av2 and U133A). The study was designed to mimic potential clinical applications by using multiple operators, machines, and reagent lots, and by performing analyses throughout a period of several months. A mixed model analysis was used to evaluate the relative contributions of multiple factors to overall variability, including operator, instrument, run, cRNA/cDNA synthesis, and changes in reagent lots. Under these conditions, the average probeset coefficient of variation (CV) was relatively low for present probesets on both generations of chips (mean coefficient of variation, 21.9% and 27.2% for U95Av2 and U133A chips, respectively). The largest contribution to overall variation was chip-to-chip (residual) variability, which was responsible for between 40 to 60% of the total variability observed. Changes in individual reagent lots and instrumentation contributed very little to the overall variability. We conclude that the approach demonstrated here could be applied to clinical validation of Affymetrix-based assays and that the analytical precision of this technique is sufficient to answer many biological questions.