MS-based quantitative proteomics plays an increasingly important role in biological and medical research and the development of these techniques remains one of the most important challenges in mass spectrometry. Numerous stable isotope labeling approaches have been proposed. However, and particularly in the case of (18)O-labeling, a standard protocol of general applicability is still lacking, and statistical issues associated to these methods remain to be investigated. In this work we present an improved high-throughput quantitative proteomics method based on whole proteome concentration by SDS-PAGE, optimized in-gel digestion, peptide (18)O-labeling, and separation by off-gel isoelectric focusing followed by liquid chromatography-LIT-MS. We demonstrate that the off-gel technique is fully compatible with (18)O peptide labeling in any pH range. A recently developed statistical model indicated that partial digestions and methionine oxidation do not alter protein quantification and that variances at the scan, peptide, and protein levels are stable and reproducible in a variety of proteomes of different origin. We have also analyzed the dynamic range of quantification and demonstrated the practical utility of the method by detecting expression changes in a model of activation of Jurkat T-cells. Our protocol provides a general approach to perform quantitative proteomics by (18)O-labeling in high-throughput studies, with the added value that it has a validated statistical model for the null hypothesis. To the best of our knowledge, this is the first report where a general protocol for stable isotope labeling is tested in practice using a collection of samples and analyzed at this degree of statistical detail.