LipostarMSI: Comprehensive, Vendor-Neutral Software for Visualization, Data Analysis, and Automated Molecular Identification in Mass Spectrometry Imaging

Sara Tortorella*, Paolo Tiberi, Andrew P. Bowman, Britt S. R. Claes, Klara Scupakova, Ron M. A. Heeren, Shane R. Ellis, Gabriele Cruciani

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

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.

Original languageEnglish
Pages (from-to)155-163
Number of pages9
JournalJournal of the American Society for Mass Spectrometry
Volume31
Issue number1
DOIs
Publication statusPublished - Jan 2020

Keywords

  • mass spectrometry imaging
  • bioinformatics
  • metabolomics
  • lipidomics
  • chemometrics
  • SPATIAL SEGMENTATION
  • ELECTROSPRAY-IONIZATION
  • HIGH-RESOLUTION
  • BREAST-CANCER
  • R PACKAGE
  • MALDI
  • TISSUE
  • MS
  • CLASSIFICATION
  • DISCOVERY

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