A Markov Chain Monte Carlo Method for Estimating the Statistical Significance of Proteoform Identifications by Top-Down Mass Spectrometry
| Autor: | Liangliang Sun, Xiaowen Liu, Qiang Kou, Zhe Wang, Si Wu, Rachele A. Lubeckyj |
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| Rok vydání: | 2019 |
| Předmět: |
Proteomics
0301 basic medicine Proteome Computer science Datasets as Topic Mass spectrometry Biochemistry Article 03 medical and health sciences symbols.namesake Software Tandem Mass Spectrometry Humans Greedy algorithm 030102 biochemistry & molecular biology Markov chain business.industry Proteins Markov chain Monte Carlo General Chemistry Top-down and bottom-up design Random walk Markov Chains Variable (computer science) 030104 developmental biology MCF-7 Cells symbols business Monte Carlo Method Protein Processing Post-Translational Algorithm Algorithms |
| Zdroj: | Journal of Proteome Research. 18:878-889 |
| ISSN: | 1535-3907 1535-3893 |
| DOI: | 10.1021/acs.jproteome.8b00562 |
| Popis: | Top-down mass spectrometry is capable of identifying whole proteoform sequences with multiple post-translational modifications because it generates tandem mass spectra directly from intact proteoforms. Many software tools, such as ProSightPC, MSPathFinder, and TopMG, have been proposed for identifying proteoforms with modifications. In these tools, various methods are employed to estimate the statistical significance of identifications. However, most existing methods are designed for proteoform identifications without modifications, and the challenge remains for accurately estimating the statistical significance of proteoform identifications with modifications. Here we propose TopMCMC, a method that combines a Markov chain random walk algorithm and a greedy algorithm for assigning statistical significance to matches between spectra and protein sequences with variable modifications. Experimental results showed that TopMCMC achieved high accuracy in estimating E-values and false discovery rates of identifications in top-down mass spectrometry. Coupled with TopMG, TopMCMC identified more spectra than the generating function method from an MCF-7 top-down mass spectrometry data set. |
| Databáze: | OpenAIRE |
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