scholarly journals Data Processing Pipeline for Lipid Profiling of Carotid Atherosclerotic Plaque with Mass Spectrometry Imaging

2019 ◽  
Vol 30 (9) ◽  
pp. 1790-1800 ◽  
Author(s):  
Mirjam Visscher ◽  
Astrid M. Moerman ◽  
Peter C. Burgers ◽  
Heleen M. M. Van Beusekom ◽  
Theo M. Luider ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Processing ◽  
Atherosclerotic Plaque ◽  
Mass Spectrometry Imaging ◽  
Carotid Atherosclerotic Plaque ◽  
Lipid Profiling ◽  
Processing Pipeline

Human carotid atherosclerotic plaque characterization by MALDI mass spectrometry imaging

2020 ◽  
Vol 315 ◽  
pp. e84-e85
Author(s):  
M. Visscher ◽  
A.M. Moerman ◽  
N. Slijkhuis ◽  
K. Van Gaalen ◽  
H.M.M. Van Beusekom ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Atherosclerotic Plaque ◽  
Mass Spectrometry Imaging ◽  
Maldi Mass Spectrometry ◽  
Carotid Atherosclerotic Plaque ◽  
Plaque Characterization ◽  
Human Carotid ◽  
Maldi Mass Spectrometry Imaging

A graphical data processing pipeline for mass spectrometry imaging-based spatially resolved metabolomics on tumor heterogeneity

2019 ◽  
Vol 1077 ◽  
pp. 183-190 ◽  
Author(s):  
Luojiao Huang ◽  
Xinxin Mao ◽  
Chenglong Sun ◽  
Zhigang Luo ◽  
Xiaowei Song ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Processing ◽  
Tumor Heterogeneity ◽  
Mass Spectrometry Imaging ◽  
Processing Pipeline ◽  
Spatially Resolved ◽  
Graphical Data

Three-Dimensional Mass Spectrometry Imaging Of Lipids In Mouse Aortic Atherosclerotic Plaque

2019 ◽  
Vol 287 ◽  
pp. e29
Author(s):  
J. Cao ◽  
P. Goossens ◽  
M. Martin-Lorenzo ◽  
K. Ščupáková ◽  
F. Dewez ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Atherosclerotic Plaque ◽  
Mass Spectrometry Imaging ◽  
Three Dimensional

scholarly journals Data Processing for 3D Mass Spectrometry Imaging

2012 ◽  
Vol 23 (6) ◽  
pp. 1147-1156 ◽  
Author(s):  
Xingchuang Xiong ◽  
Wei Xu ◽  
Livia S. Eberlin ◽  
Justin M. Wiseman ◽  
Xiang Fang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Processing ◽  
Mass Spectrometry Imaging

scholarly journals rMSIproc: an R package for mass spectrometry imaging data processing

2020 ◽  
Vol 36 (11) ◽  
pp. 3618-3619 ◽  
Author(s):  
Pere Ràfols ◽  
Bram Heijs ◽  
Esteban del Castillo ◽  
Oscar Yanes ◽  
Liam A McDonnell ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Data Processing ◽  
Mass Spectrometry Imaging ◽  
R Package ◽  
Supplementary Information ◽  
Imaging Data ◽  
Full Data ◽  
Modern Computer ◽  
Multiple Datasets ◽  
Novel Strategy

Abstract Summary Mass spectrometry imaging (MSI) can reveal biochemical information directly from a tissue section. MSI generates a large quantity of complex spectral data which is still challenging to translate into relevant biochemical information. Here, we present rMSIproc, an open-source R package that implements a full data processing workflow for MSI experiments performed using TOF or FT-based mass spectrometers. The package provides a novel strategy for spectral alignment and recalibration, which allows to process multiple datasets simultaneously. This enables to perform a confident statistical analysis with multiple datasets from one or several experiments. rMSIproc is designed to work with files larger than the computer memory capacity and the algorithms are implemented using a multi-threading strategy. rMSIproc is a powerful tool able to take full advantage of modern computer systems to completely develop the whole MSI potential. Availability and implementation rMSIproc is freely available at https://github.com/prafols/rMSIproc. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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