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

Guo Ci Teo1, Daniel A Polasky1, Fengchao Yu1

  • 1Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States.

Journal of Proteome Research
|December 17, 2020
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Summary
This summary is machine-generated.

Deisotoping, a method to simplify mass spectra by removing heavy isotope peaks, enhances proteomics analysis. Integrating this into the MSFragger engine significantly speeds up database searches and improves performance, especially for complex proteomic datasets.

Keywords:
MSFraggerdeisotopingnonspecific searchopen searchpreprocessingproteomicsspectrum processing

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Bioinformatics

Background:

  • Deisotoping is a crucial technique in proteomics for simplifying mass spectra by removing naturally occurring heavy isotope peaks.
  • This simplification aims to reduce complexity and enhance the accuracy of spectral annotation methods.
  • Previous versions of the MSFragger search engine did not incorporate deisotoping.

Purpose of the Study:

  • To develop and integrate a high-speed, parallelized deisotoping algorithm into the MSFragger proteomics search engine.
  • To evaluate the impact of this new deisotoping method on database search speed and performance.
  • To assess the performance of the deisotoping algorithm across various instrument types and vendors.

Main Methods:

  • Developed a novel, high-speed parallelized deisotoping algorithm, drawing from existing methodologies.
  • Integrated this algorithm into the existing MSFragger search engine for proteomics data analysis.
  • Tested the enhanced MSFragger on diverse datasets from multiple instrument platforms.

Main Results:

  • The integration of deisotoping into MSFragger led to substantial improvements in database search speed.
  • Performance enhancements were particularly notable for complex search strategies, including open and nonspecific searches.
  • Evaluations across different instrument types revealed variability in deisotoping performance.

Conclusions:

  • The newly incorporated deisotoping algorithm significantly boosts the efficiency and performance of the MSFragger engine.
  • Deisotoping is a valuable addition for accelerating and refining proteomic database searches, especially in challenging scenarios.
  • The findings provide an updated perspective on the utility and performance characteristics of deisotoping in contemporary proteomics.