ITRAQ data interpretation

Abstract

Quantitative proteomic analysis can help elucidating unexplored biological questions; it, however, relies on highly reproducible experiments and reliable data processing. Among the existing strategies, iTRAQ is known as an easy to use method allowing relative comparison of up to eight multiplexed samples. Once the data is acquired it is important that the final protein quantification reflects the actual amounts in the samples. Data interpretation must thus be achieved with a constant focus on quality. Here, we describe a workflow for processing iTRAQ data in user-friendly environments with emphasis on quality control. © 2012 Springer Science+Business Media, LLC.