Deleted:Heatmaps of Expression Values for Seurat Clusters - Integrated, SCT or RNA
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3 months ago
kebl4660 ▴ 10


Would greatly appreciate any help I can get!


I started by integrating scRNA-seq patient tumour tissue samples following Seurat's SCT integration pipeline as described here:

I then had a Seurat object with 3 assays (SCT, Integrated, RNA).

I clustered my populations and isolated my cells of interest, subsetting to get a new Seurat object.

Re-integrated and re-clustered the isolated population of cells.


I now want to create heatmaps of gene expression in order to compare my different sub-populations i.e. compare clusters.

I saw we can use AverageExpression as described there:

In the tutorial they use the RNA slot which is giving me a lot of infinite values with the warning message: In PseudobulkExpression(object = object, pb.method = "average", : Exponentiation yielded infinite values. data may not be log-normed.

On GitHub some suggest to use SCT if this happens:

But when I try to do DoHeatmap with SCT I get: Error in DoHeatmap(tCellsIntegratedClusterAverages, features = c("TMEM52", : No requested features found in the slot for the integrated assay. And not just for TMEM52 but for every gene I try though they are in the 'rownames' of the SCT assay.

I have read through multiple forums on Biostars and GitHub but still not sure what the best method is - should we be using SCT, Integrated or RNA for this and if SCT then why may I be getting the error mentioned above? And if RNA, should we run NormalizeData on the RNA assay before AverageExpression or not?

Thank you in advance!!!

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