Aggregate gene expression

Question

[Anst]

Hello!

I am quite new in single cell bioinformatics. I am studying Seurat. After I did data normalization and scaling, I would like to run AggregateExpression function. But the thing is that the expression is log Normal, which means that if I sum these values, I will lose the distribution.

The question is: if I am allowed to use this function after normalization + scaling or not? I am really confused...

Thanks in advance

[jv]

read the documentation for AggregateExpression https://satijalab.org/seurat/reference/aggregateexpression

If slot is set to 'data', this function assumes that the data has been log normalized and therefore feature values are exponentiated prior to aggregating so that sum is done in non-log space. Otherwise, if slot is set to either 'counts' or 'scale.data', no exponentiation is performed prior to aggregating If return.seurat = TRUE and slot is not 'scale.data', aggregated values are placed in the 'counts' slot of the returned object and the log of aggregated values are placed in the 'data' slot. For the ScaleData is then run on the default assay before returning the object. If return.seurat = TRUE and slot is 'scale.data', the 'counts' slot is left empty, the 'data' slot is filled with NA, and 'scale.data' is set to the aggregated values.