MAVEN2: An Updated Open-Source Mass Spectrometry Exploration Platform.
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ABSTRACT:
SUBMITTER: Seitzer P
PROVIDER: S-EPMC9330773 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:<p>MAVEN, an open-source software program for analysis of LC-MS metabolomics data, was originally released in 2010. As mass spectrometry has advanced in the intervening years, MAVEN has been periodically updated to reflect this advancement. This manuscript describes a major update to the program, MAVEN2, which supports LC-MS/MS analysis of metabolomics and lipidomics samples. We have developed algorithms to support MS/MS spectral matching and efficient search of large-scale fragmentation libraries. We explore the ability of our approach to separate authentic from spurious metabolite identifications using a set of standards spiked into water and yeast backgrounds. To support our improved lipid identification workflow, we introduce a novel <em>in-silico</em> lipidomics library covering major lipid classes and compare searches using our novel library to searches with existing <em>in-silico</em> lipidomics libraries. MAVEN2 source code and cross-platform application installers are freely available for download from GitHub under a GNU permissive license [ver 3], as are the in silico lipidomics libraries and corresponding code repository.</p>
2024-07-22 | MTBLS3097 | MetaboLights
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Project description:Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging due to the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MSn proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox). The program introduces ‘SmallGlyPep’ as a minimal linear representation of glycopeptides for MSn data analysis. It enables MS/MS analysis of N- and O-linked glycosylation using a novel scoring scheme to rank the hits based on cross-correlation and probability based analysis. False discovery calculations, parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to analyze site-specific glycosylation on simple glycoproteins, protein mixtures and human plasma cryoprecipitate. The results show that the simultaneous consideration of peptide and glycan fragmentation enables high quality MS spectrum annotation in three common MS/MS fragmentation modes: CID, HCD and ETD.
2017-09-19 | PXD006031 | Pride
Project description:Lipid identification from data produced with high-throughput technologies is essential to the elucidation of the roles played by lipids in cellular function and disease. Software tools for identifying lipids from tandem mass (MS/MS) spectra have been developed, but they are often costly or lack the sophistication of their proteomics counterparts. We have developed Greazy, an open source tool for the automated identification of phospholipids from MS/MS spectra, that utilizes methods similar to those developed for proteomics. From user-supplied parameters, Greazy builds a phospholipid search space and associated theoretical MS/MS spectra. Experimental spectra are scored against search space lipids with similar precursor masses using a peak score based on the hypergeometric distribution and an intensity score utilizing the percentage of total ion intensity residing in matching peaks. The LipidLama component filters the results via mixture modeling and density estimation. We assess Greazy's performance against the NIST 2014 metabolomics library, observing high accuracy in a search of multiple lipid classes. We compare Greazy/LipidLama against the commercial lipid identification software LipidSearch and show that the two platforms differ considerably in the sets of identified spectra while showing good agreement on those spectra identified by both. Lastly, we demonstrate the utility of Greazy/LipidLama with different instruments. We searched data from replicates of alveolar type 2 epithelial cells obtained with an Orbitrap and from human serum replicates generated on a quadrupole-time-of-flight (Q-TOF). These findings substantiate the application of proteomics derived methods to the identification of lipids. The software is available from the ProteoWizard repository: http://tiny.cc/bumbershoot-vc12-bin64 .
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2018-10-04 | GSE112623 | GEO
Project description:Cardinal v3 is an open source software for reproducible analysis of mass spectrometry imaging experiments. A major update from its previous versions, Cardinal v3 supports most mass spectrometry imaging workflows. Its analytical capabilities include advanced data processing such as mass re-calibration, advanced statistical analyses such as single-ion segmentation and rough annotation-based classification, and memory-efficient analyses of large-scale multi-tissue experiments.
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