# Understanding PCHeatmap outputs

I am currently trying to understand the purpose of these PCHeatmaps - part of the seurat package in R:

All the online documentation I have searched for has only highlighted how it is used to observe heterogeneity in the data.. This much I understand.

My questions are:

• Are the genes in the rows of each PC plot just the most variable x number of genes defined in FindVariableGenes?
• If not, then how are each of these genes 'chosen' for use in the PCHeatmap visualization?
• What would be the different conclusions/deductions drawn from the PC1 heatmap and PC2 heatmap with regards to heterogeneity for example?
• And finally, how can these conclusions help in the analysis of scRNASeq data?

The PCHeatmap function (renamed DimHeatmap in Seurat v3) can be used to help determine the number of principal components to use in downstream analysis, as well as to visualize the top genes contributing to each PC.
You can also set the cells.use parameter (renamed cells in Seurat v3) to only show the top n cells for each PC which can help with visualization.