Using pearson residuals for differential gene analysis

Hello. I have 6samples (3 conditions, 2 replicates for each condition).
I am trying to conduct differential gene analysis between the conditions.
One of my sample has a significantly low count overall, so I would like to remove this variation, utilizing sc.experimental.pp.normalize_pearson_residuals().
However, I am not confident if it is okay to use pearson normalized matrix for DGE analysis.
I notice that this normalization method is similar to Seurat’s SCTransform, but SCTransform datas go through PrepSCTFindMarkers() before DGE analysis, which I understand as a process of merging seperate SCT models.
Will this process be necessary for Pearson residual normalized data as well, if I want to conduct a DGE analysis?

If there are any other suggestions for regressing out ‘total counts’ before DGE analysis, I would also appreciate that.
Thank you.