4.4 Article

massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

Journal

METABOLOMICS
Volume 13, Issue 11, Pages -

Publisher

SPRINGER
DOI: 10.1007/s11306-017-1252-5

Keywords

Mass spectrometry imaging; Lipidomics; Bioinformatics software; Data processing

Funding

  1. Medical Research Council [MC UP A90 1006, MC PC 13030]
  2. Biotechnology and Biological Sciences Research Council [BB/P028195/1, BB/L024152/1, BB/M027252/2, BB/M027252/1] Funding Source: researchfish
  3. Medical Research Council [MC_UP_A090_1006, MR/P01836X/1, MC_EX_G0800783, MR/P011705/1] Funding Source: researchfish
  4. BBSRC [BB/P028195/1, BB/L024152/1, BB/M027252/2, BB/M027252/1] Funding Source: UKRI
  5. MRC [MR/P01836X/1, MC_UP_A090_1006, MR/P011705/1, MC_EX_G0800783] Funding Source: UKRI

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Introduction Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. Objectives We have developed massPix-an R package for analysing and interpreting data from MSI of lipids in tissue. Methods massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries. Results Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering. Conclusion massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.

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