The R shiny app CsppaRshiny performs machine learning analysis and visualization of cellular spatial point patterns under hypercaloric diet shifts and it is based on Csppa R-package.
The application performs 3D and 2D to visualize spatial point pattern density plots, allowing flexibility to represent the data and emphasize the question of interest. Further, it allows for performing overall and local significance analysis of spatial point pattern densities, employing several statistical approaches.
K Nearest Neighbour and Random Forest classification algorithms are implemented to compare the grouping of the cells expressing different markers within and between the diets. On top of this, correlation and spatial auto-correlation of the cells expressing different markets can be compared using the Mentel and Moran I tests, respectively.
Here we focus on the astrocytes from the arcuate nucleus of the mouse brain and the expression of Gfap and Aldh1l1 genes recovering spatial point patterns under a standard chow (SC), 5 and 15-day high-fat high sugar (HFHS) diet. The R-package Csppa allows for assessing whether these astrocyte populations are spatially organized and whether tend to form local identical clusters in response to an HFHS diet over time. To do that, the algorithm measures the degree of spatial coherence (depicting the level of similarity between neighbors) of each astrocytic sub-type in different conditions (SC, 5d, or 15d HFHS diet) by applying Moran I spatial autocorrelation coefficient, previously described as an indicator of the level of spatial dispersion. On top of that, employing a random forest classifier determines the partitioning of the feature space shared by astrocytes expressing Gfap and Aldh1l1 in each experimental group.
If you downloaded the CsppaRshiny app locally, have all the dependencies, and wish to run it, open the app.R file in RStudio and click the Run App button. You need to load functions from the R folder into RStudio before running the CsppaRshiny app or you need to install the R-package Csppa.
Data required for cellular spatial point pattern analysis will be deposited online soon:
| Data type | Link to the data | Code to get the data |
|---|---|---|
| Aldh1l1 only | link | link |
| Gfap only | link | link |
| Double positive | link | link |
Please see the following notebook for detailed examples of what you can do with CsppaRshiny:
CsppaRshiny is distributed under the MIT license. The information about the license of CsppaRshiny can be found in the LICENSE file. Please read the license before using CsppaRshiny.
Publications related to CsppaRshiny include:
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Lutomska, L.M., Miok, V., Krahmer, N., González García, I., Gruber, T., Le Thuc, O., De Bernardis Murat, C., Legutko, B., Sterr, M., Saher, G., Lickert, H., Ussar, S., Tschöp, M., Lutter, D., García-Cáceres, C. (2022), Diet triggers specific responses of hypothalamic astrocytes in time and region dependent manner, Glia 70 (10), 1795-2008.
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Lutomska, L.M., Miok, V., Krahmer, N., González García, I., Gruber, T., Le Thuc, O., De Bernardis Murat, C., Legutko, B., Sterr, M., Saher, G., Lickert, H., Ussar, S., Tschöp, M., Lutter, D., García-Cáceres, C.(2021), Hypercaloric diet selectively triggers a transient molecular rearrangement of astrocytes in the arcuate nucleus, bioRxiv, 4(1).
Please cite the relevant publications if you use CsppaRshiny.