Dynalogo: an interactive sequence logo with dynamic thresholding of matched quantitative proteomic data.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
01 03 2020
01 03 2020
Historique:
received:
30
04
2019
revised:
10
09
2019
accepted:
10
10
2019
pubmed:
15
10
2019
medline:
18
9
2020
entrez:
15
10
2019
Statut:
ppublish
Résumé
Current web-based sequence logo analyses for studying domain-peptide interactions are often conducted only on high affinity binders due to conservative data thresholding. We have developed Dynalogo, a combination of threshold varying tool and sequence logo generator written in the R statistical programming language, which allows on-the-fly visualization of binding specificity over a wide range of affinity interactions. Hence researchers can easily explore their dataset without the constraint of an arbitrary threshold. After importing quantitative data files, there are various data filtering and visualizing features available. Using a threshold control, users can easily track the dynamic change of enrichment and depletion of amino acid characters in the sequence logo panel. The built-in export function allows downloading filtered data and graphical outputs for further analyses. Dynalogo is optimized for analysis of modular domain-peptide binding experiments but the platform offers a broader application including quantitative proteomics. Dynalogo application, user manual and sample data files are available at https://dynalogo.cam.uchc.edu. The source code is available at https://github.com/lafontaine-uchc/dynalogo. Supplementary data are available at Bioinformatics online.
Identifiants
pubmed: 31609429
pii: 5586980
doi: 10.1093/bioinformatics/btz766
pmc: PMC7523650
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1632-1633Subventions
Organisme : NCI NIH HHS
ID : U01 CA154966
Pays : United States
Informations de copyright
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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