Latin square dataset for evaluating the accuracy of mass spectrometry-based protein identification and quantification

Tandem mass spectrometry-based iTRAQ protein quantification provides a powerful means for identifying disease biomarkers and plays an important role in developing new diagnosis and prognosis, new treatment, and personalised medicine. However, analyses of iTRAQ data encounter a number of statistical and computational challenges such as accurate protein identification, imputation of missing values, appropriate summarisation of protein quantification, among others. Therefore, a good evaluation dataset where raw spectra are provided, and actual composition and concentrations of the protein mixture are known, will enable better methodological development in this field. Unfortunately, there are limited evaluation datasets and existing ones are not sufficient for systematic evaluation of the existing analysis methods. To this end, we designed and performed a new Latin Square experiment that can be used for validating the accuracy of both protein identification and protein quantification.