Back to Search
Start Over
MassyTools: A High-Throughput Targeted Data Processing Tool for Relative Quantitation and Quality Control Developed for Glycomic and Glycoproteomic MALDI-MS.
- Source :
-
Journal of proteome research [J Proteome Res] 2015 Dec 04; Vol. 14 (12), pp. 5088-98. Date of Electronic Publication: 2015 Nov 13. - Publication Year :
- 2015
-
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 ).
Details
- Language :
- English
- ISSN :
- 1535-3907
- Volume :
- 14
- Issue :
- 12
- Database :
- MEDLINE
- Journal :
- Journal of proteome research
- Publication Type :
- Academic Journal
- Accession number :
- 26565759
- Full Text :
- https://doi.org/10.1021/acs.jproteome.5b00658