ArticleJournal of proteome research2016
BatMass: a Java Software Platform for LC-MS Data Visualization in Proteomics and Metabolomics.
Article in Journal of proteome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- ProteoPlotter: An Executable Proteomics Visualization Tool Compatible with Perseus.Journal of proteome research · 2025Article
- Rapid QC-MS: Interactive Dashboard for Synchronous Mass Spectrometry Data Acquisition Quality Control.Analytical chemistry · 2024Article
- AdductHunter: identifying protein-metal complex adducts in mass spectra.Journal of cheminformatics · 2024Article
- Top-down proteomics.Nature reviews. Methods primers · 2024Article
- TopMSV: A Web-Based Tool for Top-Down Mass Spectrometry Data Visualization.Journal of the American Society for Mass Spectrometry · 2021Article
- Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant.Molecular & cellular proteomics : MCP · 2020Article
- ProteomicsBrowser: MS/proteomics data visualization and investigation.Bioinformatics (Oxford, England) · 2019Article
- PDV: an integrative proteomics data viewer.Bioinformatics (Oxford, England) · 2019Article
- psims - A Declarative Writer for mzML and mzIdentML for Python.Molecular & cellular proteomics : MCP · 2019Article
- mzStudio: A Dynamic Digital Canvas for User-Driven Interrogation of Mass Spectrometry Data.Proteomes · 2017Article
- From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics.GigaScience · 2017Review
- MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics.Nature methods · 2017Article
- MathIOmica-MSViewer: a dynamic viewer for mass spectrometry files for Mathematica.Journal of mass spectrometry : JMS · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Mass spectrometry (MS) coupled to liquid chromatography (LC) is a commonly used technique in metabolomic and proteomic research. As the size and complexity of LC-MS-based experiments grow, it becomes increasingly more difficult to perform quality control of both raw data and processing results. In a practical setting, quality control steps for raw LC-MS data are often overlooked, and assessment of an experiment's success is based on some derived metrics such as "the number of identified compounds". The human brain interprets visual data much better than plain text, hence the saying "a picture is worth a thousand words". Here, we present the BatMass software package, which allows for performing quick quality control of raw LC-MS data through its fast visualization capabilities. It also serves as a testbed for developers of LC-MS data processing algorithms by providing a data access library for open mass spectrometry file formats and a means of visually mapping processing results back to the original data. We illustrate the utility of BatMass with several use cases of quality control and data exploration.
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Registered trials
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