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 ◽  
...  

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.

Metabolomics ◽  
2017 ◽  
Vol 13 (11) ◽  
Author(s):  
Nicholas J. Bond ◽  
Albert Koulman ◽  
Julian L. Griffin ◽  
Zoe Hall

2018 ◽  
Vol 17 (3) ◽  
pp. 1054-1064 ◽  
Author(s):  
Walid M. Abdelmoula ◽  
Nicola Pezzotti ◽  
Thomas Hölt ◽  
Jouke Dijkstra ◽  
Anna Vilanova ◽  
...  

2018 ◽  
Vol 35 (1) ◽  
pp. 178-180 ◽  
Author(s):  
Paolo Inglese ◽  
Gonçalo Correia ◽  
Zoltan Takats ◽  
Jeremy K Nicholson ◽  
Robert C Glen

2018 ◽  
Vol 29 (12) ◽  
pp. 2467-2470 ◽  
Author(s):  
Måns Ekelöf ◽  
Kenneth P. Garrard ◽  
Rika Judd ◽  
Elias P. Rosen ◽  
De-Yu Xie ◽  
...  

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