Parallel processing of large datasets from nanoLC-FTICR-MS measurements

Y.E.M. van der Burgt, I.M. Taban, M. Konijnenburg, M. Biskup, M.C. Duursma, R.M.A. Heeren, A. Rompp, R.V. van Nieuwpoort, H.E. Bal

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

A new approach for automatic parallel processing of large mass spectral datasets in a distributed computing environment is demonstrated to significantly decrease the total processing time. The implementation of this novel approach is described and evaluated for large nanoLC-FTICR-MS datasets. The speed benefits are determined by the network speed and file transfer protocols only and allow almost real-time analysis of complex data (e.g., a 3-gigabyte raw dataset is fully processed within 5 min). Key advantages of this approach are not limited to the improved analysis speed, but also include the improved flexibility, reproducibility, and the possibility to share and reuse the pre- and postprocessing strategies. The storage of all raw data combined with the massively parallel processing approach described here allows the scientist to reprocess data with a different set of parameters (e.g., apodization, calibration, noise reduction), as is recommended by the proteomics community. This approach of parallel processing was developed in the Virtual Laboratory for e-Science (VL-e), a science portal that aims at allowing access to users outside the computer research community. As such, this strategy can be applied to all types of serially acquired large mass spectral datasets such as LC-MS, LC-MS/MS, and high-resolution imaging MS results. © 2007 American Society for Mass Spectrometry.
Original languageEnglish
Pages (from-to)152-161
JournalJournal of the American Society for Mass Spectrometry
Volume18
DOIs
Publication statusPublished - 2007

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Processing
Distributed computer systems
Noise abatement
Proteomics
Calibration
Mass spectrometry
Noise
Mass Spectrometry
Imaging techniques
Datasets
Research

Bibliographical note

burgt07:_paral_fticr_ms

Cite this

van der Burgt, Y. E. M., Taban, I. M., Konijnenburg, M., Biskup, M., Duursma, M. C., Heeren, R. M. A., ... Bal, H. E. (2007). Parallel processing of large datasets from nanoLC-FTICR-MS measurements. Journal of the American Society for Mass Spectrometry, 18, 152-161. https://doi.org/10.1016/j.jasms.2006.09.005
van der Burgt, Y.E.M. ; Taban, I.M. ; Konijnenburg, M. ; Biskup, M. ; Duursma, M.C. ; Heeren, R.M.A. ; Rompp, A. ; van Nieuwpoort, R.V. ; Bal, H.E. / Parallel processing of large datasets from nanoLC-FTICR-MS measurements. In: Journal of the American Society for Mass Spectrometry. 2007 ; Vol. 18. pp. 152-161.
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Parallel processing of large datasets from nanoLC-FTICR-MS measurements. / van der Burgt, Y.E.M.; Taban, I.M.; Konijnenburg, M.; Biskup, M.; Duursma, M.C.; Heeren, R.M.A.; Rompp, A.; van Nieuwpoort, R.V.; Bal, H.E.

In: Journal of the American Society for Mass Spectrometry, Vol. 18, 2007, p. 152-161.

Research output: Contribution to JournalArticleAcademicpeer-review

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AU - Duursma, M.C.

AU - Heeren, R.M.A.

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AU - Bal, H.E.

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