MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA—hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data, and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA’s bootstrap DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies—BoxCar acquisition and trapped ion mobility spectrometry—both lead to deep and accurate proteome quantification.

MaxQuant.Live builds on the fast application programming interface of quadrupole Orbitrap mass analyzers to control data acquisition in real-time (freely available at www.maxquant.live ). Its graphical user interface enables advanced data acquisition strategies, such as in-depth characterization of peptides of interest. Online recalibration in mass, retention time, and intensity dimensions extends this concept to more than 25,000 peptides per run. Our “global targeting” strategy combines the best of targeted and shotgun approaches.

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Major aims of single-cell proteomics include increasing the consistency, sensitivity, and depth of protein quantification, especially for proteins and modifications of biological interest. To simultaneously advance all of these aims, we developed prioritized Single Cell ProtEomics (pSCoPE). pSCoPE ensures duty-cycle time for analyzing prioritized peptides across all single cells (thus increasing data consistency) while analyzing identifiable peptides at full duty-cycle, thus increasing proteome depth. These strategies increased the quantified data points for challenging peptides and the overall proteome coverage about 2-fold. pSCoPE enabled quantifying proteome polarization in primary mouse macrophages and linking it to phenotypic variability in endocytic activity. Proteins annotated to phagosome maturation and proton transport showed concerted variation for both untreated and lipopolysaccharide-treated macrophages, indicating a conserved axis of polarization. pSCoPE further quantified proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is easily accessible and likely to benefit many applications, especially mechanistic analysis seeking to focus on proteins of interest without sacrificing proteome coverage.