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Dinner Short Courses*


Sunday, April 3, 5:00-8:00 pm

(SC1) Data Normalization Challenges and Solutions

Christos Argyropoulos, M.D., MS, Ph.D., Assistant Professor, Nephrology, Department of Internal Medicine, University of New Mexico School of Medicine

Matthew Roth, Ph.D., Assistant Professor & Co-Director, Bioinformatics Research Lab, Baylor College of Medicine; Data Management & Resource Repository of the Extracellular RNA Consortium (NIH)

Joel Rozowsky, Ph.D., Research Scientist, Molecular Biophysics & Biochemistry, Yale University

Robert Kitchen, Ph.D., Postdoctoral Associate, Bioinformatics, Yale University School of Medicine

Normalization is a critical step in the analyses of microRNA quantification profiles, since it guarantees statistically valid inferences. To date, a number of normalization approaches have been proposed, yet a comprehensive framework to put them on a sound footing is lacking. This workshop will provide an overview of statistical approaches to normalization of microarray, qPCR and NGS microRNA data for differential expression experimental designs. We will compare different normalization approaches on the multi-platform microRNA Quality Control (miRQC) dataset and explore the impact of different normalization methods on downstream inferences. Finally, we will present a case study in which the proposed framework facilitates the synthesis of multiplatform (qPCR, NGS) data in human renal disease.


*Separate registration required

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