Metabolomics

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MassPix: An R package for annotation and interpretation of mass spectrometry imaging data for lipidomics


ABSTRACT: Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. Here we have developed massPix - an R package for analysing and interpreting data from MSI of lipids in tissue. MassPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications. MassPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries. Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering. Mouse cerebellum was analysed using matrix assisted laser desorption ionisation (MALDI) MSI. The resulting MSI dataset forms the test data for massPix.

INSTRUMENT(S): LTQ Orbitrap XL (Thermo Scientific)

SUBMITTER: Zoe Hall 

PROVIDER: MTBLS487 | MetaboLights | 2017-08-31

REPOSITORIES: MetaboLights

Dataset's files

Source:
Action DRS
MTBLS487 Other
FILES Other
a_MTBLS487_imaging_zh_metabolite_profiling_mass_spectrometry.txt Txt
i_Investigation.txt Txt
metexplore_mapping.json Other
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Publications

<i>massPix</i>: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics.

Bond Nicholas J NJ   Koulman Albert A   Griffin Julian L JL   Hall Zoe Z  

Metabolomics : Official journal of the Metabolomic Society 20170921 11


<h4>Introduction</h4>Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools.<h4>Objectives</h4>We have developed <i>massPix-</i>an R package for analysing and interpreting data from MSI of lipids in tissue.<h4>Methods</h4><i>massPix</i> produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries.<h4>Results</h4>  ...[more]

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