MS Imaging
Spatial molecular maps, pixel by pixel.
A non-target imaging workflow that treats every pixel as a real spectrum, with on-tissue MS2, co-localisation and molecular networking in the same environment.
The bottleneck
Imaging data is usually analysed as pictures, not as spectra
Most imaging software renders ion images beautifully and then stops. The underlying spectra are locked away, MS2 is acquired separately if at all, and comparing two tissue sections means exporting to a third tool.
- Ion images without the MS2 evidence behind them
- Sections analysed one at a time rather than as a study
- No path from a spatial pattern to a molecular identity
The workflow
From raw files to something you can publish.
Every step ships with default settings. You may customise each one, but you don’t have to.
Import
imzML and vendor imaging formats, with every pixel kept as a real spectrum.
Detect across pixels
Mass detection and feature finding applied to the whole section rather than to an average.
Acquire on-tissue MS2
Dataset-dependent MS2 planned across the section on timsTOF fleX instruments.
Process every image together
Sections analysed in parallel as one study, not one at a time.
Co-localise
Ion images ranked by how closely their distributions track each other.
Annotate and network
Spatial patterns carried through to molecular identities in the same environment.
Capabilities
What you get out of the box.
Non-target imaging workflow
Novel non-target imaging data analysis workflow.
Every image, together
Analyse all images in parallel.
Co-localisation analysis
Identify groups using the co-localization and molecular networking tools. Co-localization analysis and results viewer.
Pixel-level raw access
Deep dive into your imaging raw data. You have access to each pixel's raw data
In the software
The co-localisation view.
Pick one ion and every other one is ranked by how closely its distribution matches. Here the two closest matches to PI 38:4 are its own isotopes, which is the check that the ranking is doing what it claims, and below them sit the other phosphatidylinositols that map to the same regions. You read the tissue, rather than scrolling a list of m/z values hoping to recognise one.
The science
The methods behind this workflow, peer-reviewed.
Resources
Go deeper on MS Imaging
We have written this up in more detail. There are one poster and one paper. One short form and all of it unlocks.
Get started
See it on your own data.
Send us a few representative files. We will build the ms imaging workflow and show you the result before you commit to anything.