Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry

Kilgour, DPA ORCID: 0000-0002-3860-7532, Hughes, S, Kilgour, SL, Mackay, CL, Palmblad, M, Tran, BQ, Goo, YA, Ernst, RK, Clarke, DJ and Goodlett, DR, 2016. Autopiquer - a Robust and Reliable Peak Detection Algorithm for Mass Spectrometry. Journal of The American Society for Mass Spectrometry. ISSN 1044-0305

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Abstract

We present a simple algorithm for robust and unsupervised peak detection by determining a noise threshold in isotopically resolved mass spectrometry data. Solving this problem will greatly reduce the subjective and time consuming manual picking of mass spectral peaks and so will prove beneficial in many research applications. The Autopiquer approach uses autocorrelation to test for the presence of (isotopic) structure in overlapping windows across the spectrum. Within each window, a noise threshold is optimized to remove the most unstructured data whilst keeping as much of the (isotopic) structure as possible. This algorithm has been successfully demonstrated for both peak detection and spectral compression on data from many different classes of mass spectrometer and for different sample types and this approach should also be extendible to other types of data that contain regularly spaced discrete peaks.

Item Type: Journal article
Publication Title: Journal of The American Society for Mass Spectrometry
Creators: Kilgour, D.P.A., Hughes, S., Kilgour, S.L., Mackay, C.L., Palmblad, M., Tran, B.Q., Goo, Y.A., Ernst, R.K., Clarke, D.J. and Goodlett, D.R.
Publisher: Springer
Date: 6 December 2016
ISSN: 1044-0305
Identifiers:
NumberType
10.1007/s13361-016-1549-zDOI
Divisions: Schools > School of Science and Technology
Depositing User: Jonathan Gallacher
Date Added: 12 Dec 2016 10:36
Last Modified: 09 Jun 2017 14:09
URI: http://irep.ntu.ac.uk/id/eprint/29324

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