Your browser doesn't support javascript.
loading
MassDash: A Web-Based Dashboard for Data-Independent Acquisition Mass Spectrometry Visualization.
Sing, Justin C; Charkow, Joshua; AlHigaylan, Mohammed; Horecka, Ira; Xu, Leon; Röst, Hannes L.
Afiliação
  • Sing JC; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
  • Charkow J; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada.
  • AlHigaylan M; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
  • Horecka I; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada.
  • Xu L; Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
  • Röst HL; Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A8, Canada.
J Proteome Res ; 23(6): 2306-2314, 2024 Jun 07.
Article em En | MEDLINE | ID: mdl-38684072
ABSTRACT
With the increased usage and diversity of methods and instruments being applied to analyze Data-Independent Acquisition (DIA) data, visualization is becoming increasingly important to validate automated software results. Here we present MassDash, a cross-platform DIA mass spectrometry visualization and validation software for comparing features and results across popular tools. MassDash provides a web-based interface and Python package for interactive feature visualizations and summary report plots across multiple automated DIA feature detection tools, including OpenSwath, DIA-NN, and dreamDIA. Furthermore, MassDash processes peptides on the fly, enabling interactive visualization of peptides across dozens of runs simultaneously on a personal computer. MassDash supports various multidimensional visualizations across retention time, ion mobility, m/z, and intensity, providing additional insights into the data. The modular framework is easily extendable, enabling rapid algorithm development of novel peak-picker techniques, such as deep-learning-based approaches and refinement of existing tools. MassDash is open-source under a BSD 3-Clause license and freely available at https//github.com/Roestlab/massdash, and a demo version can be accessed at https//massdash.streamlit.app.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Espectrometria de Massas / Algoritmos / Software / Internet Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Peptídeos / Espectrometria de Massas / Algoritmos / Software / Internet Idioma: En Ano de publicação: 2024 Tipo de documento: Article