摘要：As a technique that allows simultaneous quantitation of proteins in multiple samples, iTRAQ (isobaric Tags for Relative and Absolute Quantitation) has gained increased interest and applications in proteomics research. Despite its success, iTRAQ data present a number of statistical challenges even after the proteins and peptides are identified and the peak areas of the reported ions are estimated for peptide intensities. In this article, we review recent studies on the analysis of iTRAQ data, the computation problems involved and the nonrandom missingness in the iTRAQ data.
关键词：ITRAQ; ANOVA; nonrandom missing; Bayesian hierarchical model; mass spectrometry
