Guan, S, Burlingame, AL (2010). Data processing algorithms for analysis of high resolution MSMS spectra of peptides with complex patterns of posttranslational modifications. Mol. Cell Proteomics, 9, 5:804-10.
Aim: For a given Spectrum, Peptide, and set of PTMs, find a subset of plausible PTM modified peptide configurations and their relative abundances.
Achievements:
- Greedy algorithm, repeatedly selects maximum scoring plausible PTM configurations from set of all possible configurations.
- Relative Abundance is computed by minimizing the least square error of theoretical peak intensity based on configuration abundance and empirical intensity.
Responses:
- May not consider very similar configurations
- Will not handle overlapping peaks.
- A first attempt solution, where improvements can be made.
- Validation was lacking/non-existent.
Baliban, RC, DiMaggio, PA, Plazas-Mayorca, MD, Young, NL, Garcia, BA, Floudas, CA (2010). A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry. Mol. Cell Proteomics, 9, 5:764-79.
Aim: For a given Spectrum and x peptides, identify the PTM and localization. (With the implicit assumption that unrestricted search means a large set of plausible PTMs)
Achievements:
- ILP formulation of the problem to output candidate PTM-peptide matches with post-finagling to acquire best modified peptide matches
- Results appear excellent, with comparison to other tools.
- 5 distinct mass spec datasets.
Critiques:
- Good preprocessing policy.
- Reduce spectra to "b" ions only. This policy varies upon instrument.
- Strategy is slow, but the accuracy of results compensates.
- Unclear what "manual validation" means.
Speaker: Xiaowen
Scribe: Anand
Slides: here
