Bioinformatics Solution Inc. is proud to share our new platform, PEAKS Online, for high-throughput analysis of large-scale DDA and DIA datasets. This platform integrates spectral library search, database search, and de novo sequencing that employs deep learning-based technology to increase the sensitivity and accuracy of peptide identification. To demonstrate this, we recently published an immunopeptidomic analysis in Nature Communications that identifies 1.7-4.1 and 1.4-2.2 times more peptides from DDA and DIA data, respectively, than previously reported. In addition, six T-cell epitopes from SARS-CoV-2 were identified, which may represent promising targets for vaccine development. Given the computing power and scalability of our PEAKS Online platform, and the sensitivity and accuracy of peptide identification, we foresee major impacts on clinical research.
Xin, L., Qiao, R., Chen, X. et al. A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics. Nat Commun 13, 3108 (2022). doi:10.1038/s41467-022-30867-7
Abstract
Integrating data-dependent acquisition (DDA) and data-independent acquisition (DIA) approaches can enable highly sensitive mass spectrometry, especially for imunnopeptidomics applications. Here we report a streamlined platform for both DDA and DIA data analysis. The platform integrates deep learning-based solutions of spectral library search, database search, and de novo sequencing under a unified framework, which not only boosts the sensitivity but also accurately controls the specificity of peptide identification. Our platform identifies 5-30% more peptide precursors than other state-of-the-art systems on multiple benchmark datasets. When evaluated on immunopeptidomics datasets, we identify 1.7-4.1 and 1.4-2.2 times more peptides from DDA and DIA data, respectively, than previously reported results. We also discover six T-cell epitopes from SARS-CoV-2 immunopeptidome that might represent potential targets for COVID-19 vaccine development. The platform supports data formats from all major instruments and is implemented with the distributed high-performance computing technology, allowing analysis of tera-scale datasets of thousands of samples for clinical applications.