Fast Deisotoping Algorithm and Its Implementation in the MSFragger Search Engine

被引:88
|
作者
Teo, Guo Ci [1 ]
Polasky, Daniel A. [1 ]
Yu, Fengchao [1 ]
Nesvizhskii, Alexey, I [1 ,2 ]
机构
[1] Univ Michigan, Dept Pathol, Ann Arbor, MI 48109 USA
[2] Univ Michigan, Dept Computat Med & Bioinformat, Ann Arbor, MI 48109 USA
关键词
proteomics; deisotoping; preprocessing; spectrum processing; MSFragger; open search; nonspecific search; MASS-SPECTROMETRY; ISOTOPIC DISTRIBUTION; SHOTGUN PROTEOMICS; STATISTICAL-MODEL; IDENTIFICATION; SENSITIVITY; REDUCTION; SOFTWARE; SPECTRA; MS/MS;
D O I
10.1021/acs.jproteome.0c00544
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Deisotoping, or the process of removing peaks in a mass spectrum resulting from the incorporation of naturally occurring heavy isotopes, has long been used to reduce complexity and improve the effectiveness of spectral annotation methods in proteomics. We have previously described MSFragger, an ultrafast search engine for proteomics, that did not utilize deisotoping in processing input spectra. Here, we present a new, high-speed parallelized deisotoping algorithm, based on elements of several existing methods, that we have incorporated into the MSFragger search engine. Applying deisotoping with MSFragger reveals substantial improvements to database search speed and performance, particularly for complex methods like open or nonspecific searches. Finally, we evaluate our deisotoping method on data from several instrument types and vendors, revealing a wide range in performance and offering an updated perspective on deisotoping in the modern proteomics environment.
引用
收藏
页码:498 / 505
页数:8
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