Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-05-04

AUTHORS

Janina Oetjen, Kirill Veselkov, Jeramie Watrous, James S McKenzie, Michael Becker, Lena Hauberg-Lotte, Jan Hendrik Kobarg, Nicole Strittmatter, Anna K Mróz, Franziska Hoffmann, Dennis Trede, Andrew Palmer, Stefan Schiffler, Klaus Steinhorst, Michaela Aichler, Robert Goldin, Orlando Guntinas-Lichius, Ferdinand von Eggeling, Herbert Thiele, Kathrin Maedler, Axel Walch, Peter Maass, Pieter C Dorrestein, Zoltan Takats, Theodore Alexandrov

ABSTRACT

BackgroundThree-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms.FindingsHigh-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma.ConclusionsWith the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets. More... »

PAGES

20

References to SciGraph publications

Journal

TITLE

GigaScience

ISSUE

1

VOLUME

4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13742-015-0059-4

DOI

http://dx.doi.org/10.1186/s13742-015-0059-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021821349

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25941567


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