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Visualizing the agreement of peptide assignments between different search engines
- Source :
- Article, Journal of mass spectrometry
- Publication Year :
- 2020
- Publisher :
- WILEY, 2020.
-
Abstract
- There is a trend in the analysis of shotgun proteomics data that aims to combine information from multiple search engines to increase the number of peptide annotations in an experiment. Typically, the degree of search engine complementarity and search engine agreement is visually illustrated by means of Venn diagrams that present the findings of a database search on the level of the nonredundant peptide annotations. We argue this practice to be not fit-for-purpose since the diagrams do not take into account and often conceal the information on complementarity and agreement at the level of the spectrum identification. We promote a new type of visualization that provides insight on the peptide sequence agreement at the level of the peptide-spectrum match (PSM) as a measure of consensus between two search engines with nominal outcomes. We applied the visualizations and percentage sequence agreement to an in-house data set of our benchmark organism, Caenorhabditis elegans, and illustrated that when assessing the agreement between search engine, one should disentangle the notion of PSM confidence and PSM identity. The visualizations presented in this manuscript provide a more informative assessment of pairs of search engines and are made available as an R function in the Supporting Information.
- Subjects :
- Proteomics
01 natural sciences
Confidence agreement
law.invention
Search engine
Data visualization
Tandem Mass Spectrometry
law
data visualization
Database search engine
identity agreement
Databases, Protein
Biology
Spectroscopy
Computer. Automation
Information retrieval
010405 organic chemistry
Chemistry
business.industry
010401 analytical chemistry
0104 chemical sciences
Visualization
Search Engine
Data set
Rater concordance
Identification (information)
multiple search engines
shotgun proteomics
Complementarity (molecular biology)
Venn diagram
Peptides
business
Subjects
Details
- Language :
- English
- ISSN :
- 10765174
- Database :
- OpenAIRE
- Journal :
- Article, Journal of mass spectrometry
- Accession number :
- edsair.doi.dedup.....d067bf1b47f88062d8f56eba39bed864