HDXBoxeR: An R package for statistical analysis and visualization of multiple Hydrogen-Deuterium Exchange Mass-Spectrometry datasets of different protein states.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
30 Jul 2024
Historique:
received: 19 04 2024
revised: 18 07 2024
accepted: 29 07 2024
medline: 30 7 2024
pubmed: 30 7 2024
entrez: 30 7 2024
Statut: aheadofprint

Résumé

Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) is a powerful protein characterization technique that provides insights into protein dynamics and flexibility at the peptide level. However, analyzing HDX-MS data presents a significant challenge due to the wealth of information it generates. Each experiment produces data for hundreds of peptides, often measured in triplicate across multiple time points. Comparisons between different protein states create distinct datasets containing thousands of peptides that require matching, rigorous statistical evaluation, and visualization. Our open-source R package, HDXBoxeR, is a comprehensive tool designed to facilitate statistical analysis and comparison of multiple sets among samples and time points for different protein states, along with data visualization. HDXBoxeR is accessible as the R package (https://cran.r-project.org/web//packages/HDXBoxeR) and GitHub: mkajano/HDXBoxeR. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 39078213
pii: 7723990
doi: 10.1093/bioinformatics/btae479
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press.

Auteurs

Maria K Janowska (MK)

Department of Biochemistry, University of Washington, Seattle, WA United States.

Katherine Reiter (K)

Department of Biochemistry, University of Washington, Seattle, WA United States.
Lyterian Therapeutics, CA United States.

Pearl Magala (P)

Department of Biochemistry, University of Washington, Seattle, WA United States.

Miklos Guttman (M)

Department of Medicinal Chemistry, University of Washington, Seattle, WA United States.

Rachel E Klevit (RE)

Department of Biochemistry, University of Washington, Seattle, WA United States.

Classifications MeSH