Moreover, since different laboratories employ different combinations of tools (see Figure 1), even for the same data, capabilities of analyzing the data vary widely and results obtained in one laboratory are often difficult to reproduce in another laboratory. Another downside of the pre- or post-processing strategies and statistical modeling tools is that, since they are often not integrated into database search tools, using them complicates the analysis of MS/MS spectra. While they often improve the performance of a database search tool, their performance is negatively affected when the database search tool fails to find correct PSMs. These tools do not find new Peptide-Spectrum Matches (PSMs), but rather re-score PSMs reported by a database search tool using more complex scoring and output high-scoring PSMs. To further boost the performance, MS/MS database search tools are combined with statistical modeling tools like PeptideProphet, Percolator, and IDPicker. For example, several pre- or post-processing strategies have been proposed, resulting in small improvement in the performance of database search tools. Many efforts have been invested into making existing MS/MS search tools compatible with new types of data. While several new MS/MS database search engines were recently developed including Andromeda, Morpheus, and MS Amanda ), they have resulted in only minor improvements as compared to SEQUEST and Mascot. Unfortunately, the popular MS/MS database search tools such as SEQUEST and Mascot have not kept pace with the increased diversity of the data. Therefore, unlike in the past when low-precision Collision Induced Dissociation (CID) spectra of tryptic peptides dominated the field, spectral datasets generated today are very diverse. Depending on these choices, the resulting tandem mass (MS/MS) spectra vary in fragmentation propensities and precision. Empowered by these changes, MS researchers now have diverse choices with respect to the questions: “what fragmentation method to use?”, “how accurate should be the measurements of the mass-to-charge (m/z) ratios?”, “what proteases to use?”, and “what post-translational modification (PTM) to focus on (e.g. While trypsin remains a dominant protease in proteomics studies, digesting proteins with diverse proteases is becoming popular. New fragmentation technologies have emerged and high-precision mass spectrometers like Orbitrap have become widely available. Mass spectrometry (MS) instruments and experimental protocols have greatly advanced over the last decade. We emphasize that while MS-GF+ is not specifically designed for any particular experimental set-up, it improves upon the performance of tools specifically designed for these applications (e.g., specialized tools for phosphoproteomics). For all these datasets, MS-GF+ significantly increases the number of identified peptides compared to commonly used methods for peptide identifications. We benchmark MS-GF+ using diverse spectral datasets: (i) spectra of varying fragmentation methods (ii) spectra of multiple enzyme digests (iii) spectra of phosphorylated peptides (iv) spectra of peptides with unusual fragmentation propensities produced by a novel alpha-lytic protease. We present a database search tool MS-GF+ that is sensitive (it identifies more peptides than most other database search tools) and universal (it works well for diverse types of spectra, different configurations of MS instruments and different experimental protocols). Mass spectrometry (MS) instruments and experimental protocols are rapidly advancing, but the software tools to analyze tandem mass spectra are lagging behind.
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