title: Evaluation of proteomic search engines for the analysis of histone modifications.
abstract: Identification of histone post-translational modifications (PTMs) is challenging for proteomics search engines. Including many histone PTMs in one search increases the number of candidate peptides dramatically, leading to low search speed and fewer identified spectra. To evaluate database search engines on identifying histone PTMs, we present a method in which one kind of modification is searched each time, for example, unmodified, individually modified, and multimodified, each search result is filtered with false discovery rate less than 1%, and the identifications of multiple search engines are combined to obtain confident results. We apply this method for eight search engines on histone data sets. We find that two search engines, pFind and Mascot, identify most of the confident results at a reasonable speed, so we recommend using them to identify histone modifications. During the evaluation, we also find some important aspects for the analysis of histone modifications. Our evaluation of different search engines on identifying histone modifications will hopefully help those who are hoping to enter the histone proteomics field. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD001118.
authors.affiliation: Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania , 3400 Civic Center, Building 421, Philadelphia, Pennsylvania 19104, United States.
authors.forename: Zuo-Fei
authors.initials: ZF
authors.lastname: Yuan
authors.forename: Shu
authors.initials: S
authors.lastname: Lin
authors.forename: Rosalynn C
authors.initials: RC
authors.lastname: Molden
authors.forename: Benjamin A
authors.initials: BA
authors.lastname: Garcia
mesh_terms: D030562:Databases, Protein; D006367:HeLa Cells; D006657:Histones / Q000737:chemistry*; D006801:Humans; D040901:Proteomics; D057386:Search Engine
chemical_list: D006657:Histones
keywords: data analysis; histone; post-translational modification; proteomics; search engine