Multimodal imaging by matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI MSI) and microscopy holds potential for understanding pathological mechanisms by mapping molecular signatures from the tissue micro environment to specific cell populations. However, existing software solutions for MALDI MSI data analysis are incomplete, require programming skills and contain laborious manual steps, hindering broadly applicable, reproducible, and high throughput analysis to generate impactful biological discoveries. Here we present msiFlow, an accessible open-source, platform-independent and vendor-neutral software for end-to-end, high-throughput, transparent and reproducible analysis of multi modal imaging data. msiFlow integrates all necessary steps from raw data import to analysis visualization along with state-of-the-art and newly developed algorithms into automated workflows. Using msiFlow, we unravel the molecular heterogeneity of leukocytes in infected tissues by spatial regulation of ether-linked phospholipids containing arachidonic acid. We anticipate that msiFlow will facilitate the broad applicability of MSI in multi modal imaging to uncover context-dependent cellular regulations in disease states.
[doi:10.25345/C5HH6CJ29]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: Lipidomics, LC-MS/MS ; DatasetType:Other (Lipidomics)
Principal Investigators: (in alphabetical order) |
Dr. Prasad Phapale, Leibniz-Institut f�r Analytische Wissenschaften-ISAS-e.V., Germany |
Submitting User: | Kasarla04 |
Philippa Spangenberg, Sebastian Bessler, Lars Widera, Jenny Bottek, Mathis Richter, Stephanie Thiebes, Devon Siemes, Sascha D. Krauß, Lukasz G. Migas, Siva Swapna Kasarla, Prasad Phapale, Jens Kleesiek, Dagmar Führer, Lars C. Moeller, Heike Heuer, Raf Van de Plas, Matthias Gunzer, Oliver Soehnlein, Jens Soltwisch, Olga Shevchuk, Klaus Dreisewerd, Daniel R. Engel.
msiFlow: Automated Workflows for Reproducible and Scalable Multimodal Mass Spectrometry Imaging and Immunofluorescence Microscopy Data Processing and Analysis.
bioRxiv 2024.08.24.609403; doi: https://doi.org/10.1101/2024.08.24.609403 (Preprint).
Number of Files: | |
Total Size: | |
Spectra: | |
Subscribers: | |
Owner | Reanalyses | |
---|---|---|
Experimental Design | ||
Conditions:
|
||
Biological Replicates:
|
||
Technical Replicates:
|
||
Identification Results | ||
Proteins (Human, Remapped):
|
||
Proteins (Reported):
|
||
Peptides:
|
||
Variant Peptides:
|
||
PSMs:
|
||
Quantification Results | ||
Differential Proteins:
|
||
Quantified Proteins:
|
||
Browse Dataset Files | |
FTP Download Link (click to copy):
|