| Literature DB >> 26565759 |
Bas C Jansen1, Karli R Reiding1, Albert Bondt1,2, Agnes L Hipgrave Ederveen1, Magnus Palmblad1, David Falck1, Manfred Wuhrer1,3.
Abstract
The study of N-linked glycosylation has long been complicated by a lack of bioinformatics tools. In particular, there is still a lack of fast and robust data processing tools for targeted (relative) quantitation. We have developed modular, high-throughput data processing software, MassyTools, that is capable of calibrating spectra, extracting data, and performing quality control calculations based on a user-defined list of glycan or glycopeptide compositions. Typical examples of output include relative areas after background subtraction, isotopic pattern-based quality scores, spectral quality scores, and signal-to-noise ratios. We demonstrated MassyTools' performance on MALDI-TOF-MS glycan and glycopeptide data from different samples. MassyTools yielded better calibration than the commercial software flexAnalysis, generally showing 2-fold better ppm errors after internal calibration. Relative quantitation using MassyTools and flexAnalysis gave similar results, yielding a relative standard deviation (RSD) of the main glycan of ~6%. However, MassyTools yielded 2- to 5-fold lower RSD values for low-abundant analytes than flexAnalysis. Additionally, feature curation based on the computed quality criteria improved the data quality. In conclusion, we show that MassyTools is a robust automated data processing tool for high-throughput, high-performance glycosylation analysis. The package is released under the Apache 2.0 license and is freely available on GitHub ( https://github.com/Tarskin/MassyTools ).Entities:
Keywords: Bioinformatics; biopharmaceuticals; glycomics; glycoproteomics; mass spectrometry; matrix-assisted laser desorption/ionization; profiling; quality control; relative quantitation
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Year: 2015 PMID: 26565759 DOI: 10.1021/acs.jproteome.5b00658
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 4.466