I'm confused on Seurat's tutorial of integrating two datasets.
Seurat has this: nk.markers <- FindConservedMarkers(immune.combined, ident.1 = 7, grouping.var = "stim",print.bar = FALSE)
After I do this for every cluster, what should go into the feature plot? Seurat has this line of code, but I don't know where those genes come from. Is it the highest logFC (of conserved markers) from each cluster?
FeaturePlot(object = immune.combined, features.plot = c("CD3D", "SELL", "CREM", "CD8A", "GNLY", "CD79A", "FCGR3A", "CCL2", "PPBP"), min.cutoff = "q9", cols.use = c("lightgrey", "blue"), pt.size = 0.5)
Thanks for your help.
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Bios •
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FeaturePlot is a tool that allows you to visualize that distribution of a feature in you tSNE plot. For example if you do:
FeaturePlot(object = immune.combined, features.plot = c("CD3D"), min.cutoff = "q9", cols.use = c("lightgrey", "blue"), pt.size = 0.5)
You should see the expression level of the gene CD3D in each cell that it is expressed in. If i remember correctly you can also visualize other features from your metadata (if you have provided metadata). Something like the following should allow you to visualize the batch IDs as colors (if you provided batch IDs).
FeaturePlot(object = immune.combined, features.plot = c("batch"), min.cutoff = "q9", pt.size = 0.5)
To answer you question about how to identify cell types in the clusters... This is best done by looking for the expression of known marker genes for each cluster. You might start by looking for known markers among the list of top cluster defining genes generated for each cluster.
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