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ABSTRACT: Motivation
In proteomics, database search programs are routinely used for peptide identification from tandem mass spectrometry data. However, many low-quality spectra cannot be interpreted by any programs. Meanwhile, certain high-quality spectra may not be identified due to incompleteness of the database or failure of the software. Thus, spectrum quality (SPEQ) assessment tools are helpful programs that can eliminate poor-quality spectra before the database search and highlight the high-quality spectra that are not identified in the initial search. These spectra may be valuable candidates for further analyses.Results
We propose SPEQ: a spectrum quality assessment tool that uses a deep neural network to classify spectra into high-quality, which are worthy candidates for interpretation, and low-quality, which lack sufficient information for identification. SPEQ was compared with a few other prediction models and demonstrated improved prediction accuracy.Availability and implementation
Source code and scripts are freely available at github.com/sor8sh/SPEQ, implemented in Python.
SUBMITTER: Gholamizoj S
PROVIDER: S-EPMC8896601 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature
Bioinformatics (Oxford, England) 20220301 6
<h4>Motivation</h4>In proteomics, database search programs are routinely used for peptide identification from tandem mass spectrometry data. However, many low-quality spectra cannot be interpreted by any programs. Meanwhile, certain high-quality spectra may not be identified due to incompleteness of the database or failure of the software. Thus, spectrum quality (SPEQ) assessment tools are helpful programs that can eliminate poor-quality spectra before the database search and highlight the high- ...[more]