Maybe I have not formulated my question precisely enough as I have no intention to run DE-Seq on anything else but raw counts, but could you point me to a suitable method to analyze TPMs?

I think the OP meant to type "DE-Seq2 requires raw counts" in the first sentence. I have the same question about running basic statistical tests on counts that have NOT been normalized using DESeq2 (which performs its own stats), but have been normalized using some other method. I've seen some recent papers in which the authors plot "normalized expression" (normalized counts as log2TPM or something similar) and then run t-tests to determine significance. Is this correct/the best way to do this? If not, how do you determine if gene expression is significantly different using normalized transcript counts (i.e. data downloaded from the TCGA or data deposited as TPMs or CPMs, which are apparently not appropriate for differential expression analysis https://hbctraining.github.io/DGE_workshop/lessons/02_DGE_count_normalization.html)

Here is an example: https://www.nature.com/articles/s41598-021-85993-x/figures/2 from https://www.nature.com/articles/s41598-021-85993-x