BatMass: a Java Software Platform for LC-MS Data Visualization in Proteomics and Metabolomics.
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.
Department of Pathology, ‡BRCF Metabolomics Core, and §Department of Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor, Michigan 48109, United States.
Dmitry M
DM
Avtonomov
Department of Pathology, ‡BRCF Metabolomics Core, and §Department of Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor, Michigan 48109, United States.
Alexander
A
Raskind
Department of Pathology, ‡BRCF Metabolomics Core, and §Department of Computational Medicine and Bioinformatics, University of Michigan , Ann Arbor, Michigan 48109, United States.
Alexey I
AI
Nesvizhskii
D002853:Chromatography, Liquid; D003196:Computer Graphics; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics / Q000379:methods*; D040901:Proteomics / Q000379:methods*; D011786:Quality Control; D012984:Software
Java; LC−MS; data visualization; mass spectrometry