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NITPICK: Peak Identification for Mass Spectrometry Data

Overview
Publisher Biomed Central
Specialty Biology
Date 2008 Aug 30
PMID 18755032
Citations 37
Authors
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Abstract

Background: The reliable extraction of features from mass spectra is a fundamental step in the automated analysis of proteomic mass spectrometry (MS) experiments.

Results: This contribution proposes a sparse template regression approach to peak picking called NITPICK. NITPICK is a Non-greedy, Iterative Template-based peak PICKer that deconvolves complex overlapping isotope distributions in multicomponent mass spectra. NITPICK is based on fractional averaging, a novel extension to Senko's well-known averaging model, and on a modified version of sparse, non-negative least angle regression, for which a suitable, statistically motivated early stopping criterion has been derived. The strength of NITPICK is the deconvolution of overlapping mixture mass spectra.

Conclusion: Extensive comparative evaluation has been carried out and results are provided for simulated and real-world data sets. NITPICK outperforms pepex, to date the only alternate, publicly available, non-greedy feature extraction routine. NITPICK is available as software package for the R programming language and can be downloaded from (http://hci.iwr.uni-heidelberg.de/mip/proteomics/).

Citing Articles

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AdductHunter: identifying protein-metal complex adducts in mass spectra.

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The isotope distribution: A rose with thorns.

Claesen J, Rockwood A, Gorshkov M, Valkenborg D Mass Spectrom Rev. 2023; 44(1):22-42.

PMID: 36744702 PMC: 11624904. DOI: 10.1002/mas.21820.


Advances in Hydrogen/Deuterium Exchange Mass Spectrometry and the Pursuit of Challenging Biological Systems.

James E, Murphree T, Vorauer C, Engen J, Guttman M Chem Rev. 2021; 122(8):7562-7623.

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Fast Deisotoping Algorithm and Its Implementation in the MSFragger Search Engine.

Teo G, Polasky D, Yu F, Nesvizhskii A J Proteome Res. 2020; 20(1):498-505.

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