Signal Alignment Enables Analysis of DIA Proteomics Data from Multisite Experiments

Abstract

AbstractDIA has become a mainstream method for quantitative proteomics, however consistent quantification across multiple LC-MS/MS instruments remains a bottleneck in parallelizing the data-acquisition. To produce a highly consistent and quantitatively accurate data matrix, we have developed DIAlignR which uses raw fragment-ion chromatograms for cross-run alignment. Its performance on a gold standard annotated dataset, demonstrates a threefold reduction in the identification error-rate when compared to standard non-aligned DIA results. A similar performance is achieved for a dataset of 229 runs acquired using 11 different LC-MS/MS setups. Finally, the analysis of 949 plasma runs with DIAlignR increased the number of statistically significant proteins by 43% and 62% for insulin resistant (IR) and respiratory viral infection (RVI), respectively compared to prior analysis without it. Hence, DIAlignR fills a gap in analyzing DIA runs acquired in-parallel using different LC-MS/MS instrumentation.