| Literature DB >> 33332123 |
Guo Ci Teo1, Daniel A Polasky1, Fengchao Yu1, Alexey I Nesvizhskii1,2.
Abstract
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.Entities:
Keywords: MSFragger; deisotoping; nonspecific search; open search; preprocessing; proteomics; spectrum processing
Mesh:
Year: 2020 PMID: 33332123 PMCID: PMC8864561 DOI: 10.1021/acs.jproteome.0c00544
Source DB: PubMed Journal: J Proteome Res ISSN: 1535-3893 Impact factor: 4.466