Data-Driven Optimization of DIA Mass Spectrometry by DO-MS

Mass
spectrometry (MS) enables specific and accurate quantification
of proteins with ever-increasing throughput and sensitivity. Maximizing
this potential of MS requires optimizing data acquisition parameters
and performing efficient quality control for large datasets. To facilitate
these objectives for data-independent acquisition (DIA), we developed
a second version of our framework for data-driven optimization of
MS methods (DO-MS). The DO-MS app v2.0 (do-ms.slavovlab.net)
allows one to optimize and evaluate results from both label-free and
multiplexed DIA (plexDIA) and supports optimizations particularly
relevant to single-cell proteomics. We demonstrate multiple use cases,
including optimization of duty cycle methods, peptide separation,
number of survey scans per duty cycle, and quality control of single-cell
plexDIA data. DO-MS allows for interactive data display and generation
of extensive reports, including publication of quality figures that
can be easily shared. The source code is available at github.com/SlavovLab/DO-MS.