* The following contents are based on SCILSTMLab analysis software.
Q 1
What are the main analysis contents?
1. Spatial clustering analysis (segmentation)
The essence of spatial clustering analysis is the heat map of spatial clustering analysis. After the clustering algorithm, the areas with similar metabolic patterns are marked with the same color, and the slices are clearly and intuitively classified from the molecular level. After the whole slice analysis is completed, further cluster analysis can be carried out on the areas of concern to find more unique areas.
Application case:
2. Molecular imaging of metabolites
Analyze a single metabolite molecule to obtain a thermogram of its spatial distribution and expression. In the figure, the redder the color, the higher the expression level of metabolites, and the bluer the color, the lower the expression level of metabolites.
Application case:
Q2
How to clean data and find key metabolite molecules?
1.ROC analysis
SCILSTM？ Lab integrates machine learning algorithm, carries out ROC analysis according to the concentration and distribution of metabolites in the target area, and outputs the list of metabolites. Usually, acrometabolites have a great influence on the difference, which can be further confirmed by molecular imaging.
2. Co-location of metabolites in molecular space
Spatial co-location analysis is a spatial correlation analysis of metabolites. After selecting a target metabolite, the spatial correlation calculation is carried out, and the list of metabolites consistent with the spatial expression trend of the target metabolite is output, which can help analyze the expression pattern and metabolic network of metabolites in this area.
3. Statistical difference analysis and bioinformatics analysis of metabolites
This part of the analysis is consistent with the conventional metabonomics, mainly focusing on one-dimensional and multi-dimensional statistical analysis, KEGG pathway analysis, expression correlation analysis, cluster thermogram, metabolite classification and so on. In spatial metabonomics, the analysis target is a designated area or slice. When the target area is selected, the metabolite content in this area is integrated by algorithm, and the subsequent analysis is carried out.