LipostarMSI: Comprehensive, Vendor-Neutral Software for Visualization, Data Analysis, and Automated Molecular Identification in Mass Spectrometry Imaging.
Sara TortorellaPaolo TiberiAndrew P BowmanBritt S R ClaesKlára ŠčupákováRon M A HeerenShane R EllisGabriele CrucianiPublished in: Journal of the American Society for Mass Spectrometry (2019)
Mass Spectrometry Imaging (MSI) is an established and powerful MS technique that enables molecular mapping of tissues and cells finding widespread applications in academic, medical, and pharmaceutical industries. As both the applications and MSI technology have undergone rapid growth and improvement, the challenges associated both with analyzing large datasets and identifying the many detected molecular species have become apparent. The lack of readily available and comprehensive software covering all necessary data analysis steps has further compounded this challenge. To address this issue we developed LipostarMSI, comprehensive and vendor-neutral software for targeted and untargeted MSI data analysis. Through user-friendly implementation of image visualization and co-registration, univariate and multivariate image and spectral analysis, and for the first time, advanced lipid, metabolite, and drug metabolite (MetID) automated identification, LipostarMSI effectively streamlines biochemical interpretation of the data. Here, we introduce LipostarMSI and case studies demonstrating the versatility and many capabilities of the software.
Keyphrases
- data analysis
- mass spectrometry
- high resolution
- deep learning
- liquid chromatography
- healthcare
- gas chromatography
- machine learning
- high performance liquid chromatography
- high throughput
- capillary electrophoresis
- induced apoptosis
- primary care
- gene expression
- multiple sclerosis
- single molecule
- ms ms
- cancer therapy
- magnetic resonance
- tandem mass spectrometry
- magnetic resonance imaging
- cell cycle arrest
- bioinformatics analysis
- fatty acid
- quantum dots
- pi k akt
- medical students
- endoplasmic reticulum stress