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Title
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Visualizing the agreement of peptide assignments between different search engines
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Author
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Abstract
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| 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 non‐redundant 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 visualisation 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 dataset of our benchmark organism, C. elegans and illustrate 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 supplementary materials. |
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Language
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English
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Source (journal)
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Journal of mass spectrometry. - Chichester
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Publication
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Hoboken
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Wiley
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2019
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ISSN
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1076-5174
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DOI
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10.1002/JMS.4471
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Volume/pages
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8 p.
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ISI
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000500164600001
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Pubmed ID
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31713933
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Full text (Publisher's DOI)
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Full text (open access)
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Full text (publisher's version - intranet only)
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