MetaboAnalyst

Spatial Multi-Omics

Integrate spatial metabolomics with a second spatial omic of the same section (Visium transcriptomics, spatial proteomics): joint clustering, co-localisation, pseudobulk comparison, joint pathways and shared spatial programs.

Please upload the two layers (.csv or .txt)

A metabolite table, a gene or protein table and a spot metadata table, plus metabolite pixel coordinates when the pixels are not the spots.

Raw or TIC-scaled metabolite intensities and raw gene counts are expected. Limits: 50 MB per file, at most 100,000 spots, 5,000 metabolite features and 5,000 genes (the most variable genes are kept).

Metabolite table:	Choose
Metabolite metadata (optional):	Choose
Gene / protein table:	Choose
Spot metadata:	Choose
Metabolite features:	m/z values Compound / lipid names
ROI column:	(auto = first of ROI / group / region / cluster)
Ion mode (m/z):
Mass tolerance (ppm):
Organism / library:
Max. genes kept:

Try our example data

Mouse striatum (SMA)

One coronal mouse brain section (striatum, section V11L12-038_A1) profiled by Spatial Multimodal Analysis (Vicari et al., Nat Biotechnol 2024): MALDI-FT-ICR imaging of lipids (DHB, positive mode, 3,105 tissue pixels x 600 most variable m/z) and Visium RNA on the same section (2,856 spots x 1,012 most variable genes, counts). The MSI pixel grid was registered onto the Visium coordinates (micrometres) from the tissue outline and the region labels; the regions (cortex, caudoputamen, corpus callosum, ...) come from the authors' Loupe annotation. Source: Mendeley Data 10.17632/w7nw4km7xd.1.