CellPhoneDB [1] addresses the challenges of studying cell-cell communication in scRNA-seq and spatial data. It allows researchers to move beyond just measuring gene expression and delve into the complicated cellular communication world. By analyzing the scRNA-seq or spatial data through the lens of CellPhoneDB, researchers can identify potential signaling pathways and communication networks between different cell types within the tissue sample. Partek^® Flow^® wrapped the statistical analysis pipeline (method 2) from CellPhoneDB v5 for the [1][2] for this purpose. 

How to use CellPhoneDB in Partek Flow

Invoke the CellPhoneDB task in Flow can be invoked in Partek Flow from a normalized counts data node using the Exploratory analysis section by clicking the normalized counts data node (Figure 1). We recommend running CellPhoneDB on the log normalized data directly, particularly the log normalized data.  

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The GUI is simple and easy to understand. For each option, the grey colored description explains more details (Figure 2).  If the dataset working on is single cell RNA-Seq, no it doesn't need the Micro environment file is needed. However, if the dataset it is a spatial data, most likely you would like to provide the Micro environment file because of its spatial contents. By default, the value of 0.10 will be used as threshold to select which cells are used for the analysis in the cluster. However, the number could be adjusted manually or typed in directly.  Simply click the Finish button if you want to run the task as default.

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Double click the Output matrix data node will open the task report in Data Viewer. It is another variant of heatmap that displays how  how genes of your interest interact with each other in the defined cell type pairs (Figure 5). The exampled plot also indicates the data are from two environments. For instructions on setting up the Micro environment file for your spatial study, refer to Figure 2. CellPhoneDB analysis classifies signaling pathways for genes of interest. These classifications are then used to annotate the heatmap within the task report. 

Why are the values of clusterA-clusterB different to the values of clusterB-clusterA?

It is important to note that the interactions are not symmetric. The authors state that, "Partner A expression is considered for the first cluster/cell type (clusterA), and partner B expression is considered on the second cluster/cell type (clusterB). Thus, IL12-IL12 receptor for clusterA-clusterB (i.e. the receptor is in clusterB) is not the same as IL-12-IL-12 receptor for clusterB-clusterA (i.e. the receptor is in clusterA), and will have different values." [3][4]

Where do the interactions come from? 

The interactions come from the CellphoneDB database. It is manually curated repository using reviewed molecular interactions with demonstrated evidence for a role in cellular communication. [5] 

References

1. Troule, etc (2023). CellPhoneDB v5: Inferring cell-cell communication from single cell multiomics data. https://arxiv.org/pdf/2311.04567.pdf
2. https://github.com/ventolab/CellphoneDB 
3. https://github.com/ventolab/CellphoneDB/blob/master/docs/RESULTS-DOCUMENTATION.md 
4. https://cellphonedb.readthedocs.io/en/latest/RESULTS-DOCUMENTATION.html#why-values-of-clustera-clusterb-are-different-to-the-values-of-clusterb-clustera 
5. https://github.com/ventolab/cellphonedb-data 

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