leegwater_lipidomics_normalization
Code to generate figures for "Normalization strategies for lipidome data in cell line panels" (Leegwater et al. 2024)
https://github.com/lacdr-tox/leegwater_lipidomics_normalization
Science Score: 75.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 7 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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✓Institutional organization owner
Organization lacdr-tox has institutional domain (www.universiteitleiden.nl) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (12.9%) to scientific vocabulary
Repository
Code to generate figures for "Normalization strategies for lipidome data in cell line panels" (Leegwater et al. 2024)
Basic Info
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Metadata Files
README.md
Lipidomics in breast cancer cell lines
This repository contains code to analyze data and generate figures for the following two manuscripts:
"Leegwater, H., Zhang, Z., Zhang, X., Hankemeier, T., Harms, A. C., Zweemer, A. J. M., Le Dévédec, S. E., & Kindt, A. (2025). Normalization Strategies for Lipidome Data in Cell Line Panels. Journal of Chemometrics, 39(1), e3636. https://doi.org/10.1002/cem.3636
and:
Leegwater H., Zhang Z., Zhang X., Wang X., Hankemeier T., Zweemer A. J. M., van de Water B., Danen E., Hoekstra M., Harms A. C., Kindt A., Le Dévédec S. E. (2025). Distinct lipidomic profiles in breast cancer cell lines relate to proliferation and EMT phenotypes. Biochim Biophys Acta Mol Cell Biol Lipids. 2025 Aug 3:159679. https://doi.org/10.1016/j.bbalip.2025.159679. Epub ahead of print. PMID: 40763903.
Usage
Within the code folder, you will find R markdown files (Normalization manuscript) and Quarto files (Biological interpretation manuscript) and a functions folder. The R markdown/Quarto files can be used to rerun all code and to create all figures. Functions that one might want to reuse can be found in the functions folder.
Note that both projects were run with different versions of R and R packages. If you run into trouble with versions, the docs folder has the reports of the version used for manuscript submission, with all session info recorded.
Data
Metabolomics data have been deposited to the EMBL-EBI MetaboLights (Yurekten et al., 2024) with the identifier MTBLS9493 and is accessible at https://www.ebi.ac.uk/metabolights/MTBLS9493.
Data to rerun the analysis is in the data. Let us know if anything is missing. For examples of the output, you can take a look at the HTML reports to see what the data and results could look like.
Figures
Figures are generated reproducibly in R using renv:
Download/clone this repository
Open the project file (
.Rproj) in RStudioRun
r renv::restore()to install R package dependencies.
Open
code/Calculations_to_get_all_data_for_all_figures.Rmdand choose Run > Run All. You may need to set a custom directory for the data, since this is not yet part of this repository.Open
code/All_figures.Rmdand choose Run > Run All. Figures will appear in the specifiedoutput_dirfolder.
Acknowledgments
Thanks to \@burgerga for suggestions on publishing this repository.
Owner
- Name: LACDR-DDS - Beltman lab
- Login: lacdr-tox
- Kind: organization
- Email: j.b.beltman@lacdr.leidenuniv.nl
- Location: Leiden, The Netherlands
Assoc. Prof. Dr. Joost Beltman is head of the Image-based Computational Biology group at the LACDR Division of Drug Discovery & Safety (DDS)
Citation (CITATION.cff)
cff-version: 1.2.0
message: "Please cite the publication if you use this code, optionally together with this repository's Zenodo DOI."
authors:
- family-names: Leegwater
given-names: Hanneke
affiliation: Leiden University
orcid: https://orcid.org/0000-0001-6003-1544
- family-names: Kindt
given-names: Alida
affiliation: Leiden University
orcid: https://orcid.org/0000-0001-6551-6030
title: "Code to normalize and interpret lipidome data in breast cancer cell lines."
version: 2.0.1
date-released: 2025-08-06
identifiers:
- type: doi
value: 10.5281/zenodo.10635384
abstract: |-
Code to generate figures for: Leegwater, H., Zhang, Z., Zhang, X., Hankemeier, T., Harms, A. C., Zweemer, A. J. M., Le Dévédec, S. E., & Kindt, A. (2025). Normalization Strategies for Lipidome Data in Cell Line Panels. Journal of Chemometrics, 39(1), e3636. https://doi.org/10.1002/cem.3636 and Leegwater H., Zhang Z., Zhang X., Wang X., Hankemeier T., Zweemer A. J. M., van de Water B., Danen E., Hoekstra M., Harms A. C., Kindt A., Le Dévédec S. E. (2025). Distinct lipidomic profiles in breast cancer cell lines relate to proliferation and EMT phenotypes. Biochim Biophys Acta Mol Cell Biol Lipids. 2025 Aug 3:159679. https://doi.org/10.1016/j.bbalip.2025.159679. Epub ahead of print. PMID: 40763903.
license: MIT
preferred-citation:
title: "Normalization strategies for lipidome data in cell line panels"
type: article
authors:
- family-names: Leegwater
given-names: Hanneke
- family-names: Zhang
given-names: Zhengzheng
- family-names: Zhang
given-names: Xiaobing
- family-names: Hankemeier
given-names: Thomas
- family-names: Harms
given-names: Amy C.
- family-names: Zweemer
given-names: Annelien J. M.
- family-names: Le Dévédec
given-names: Sylvia E.
- family-names: Kindt
given-names: Alida
journal: Journal of Chemometrics
year: 2025
identifiers:
- type: doi
value: 10.1002/cem.3636
start: e3636
volume: 39
url: https://doi.org/10.1002/cem.3636
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