Efficient reduction of candidate matches in peptide spectrum library searching using the top k most intense peaks
Faculty of Sciences. Biology
Faculty of Sciences. Chemistry
Faculty of Sciences. Mathematics and Computer Science
Journal of proteome research
, p. 4175-4183
University of Antwerp
Spectral library searching is a popular approach for MS/MS-based peptide identification. Because the size of spectral libraries continues to grow, the performance of searching algorithms is an important issue. This paper introduces a strategy based on a minimum shared peak count between two spectra to reduce the set of admissible candidate spectra when issuing a query. A theoretical validation through a time complexity analysis and an experimental validation based on an implementation of the candidate reduction strategy show that the approach can achieve a reduction of the set of candidate spectra by (at least) an order of magnitude, resulting in a significant speed-up. Meanwhile, more than 99% of the positive search results are retained. This efficient strategy to drastically speed up spectral library searching with a negligible loss of sensitivity can be applied to any current spectral library search tool, irrespective of the employed similarity metric.