Happy to take any swish questions on Bioconductor by the way.
Another relevant Bioconductor tool, recently preprinted is here:
Dividing out quantification uncertainty allows efficient assessment of differential transcript expression https://www.biorxiv.org/content/10.1101/2023.04.02.535231v1
Swish doesn't have much sensitivity when the per-group replicate count is small (n=3), but this leverages edgeR so should gain sensitivity through the standard empirical Bayes procedure.
Can you say with confidence that all parameters, that means code, software versions, reference genome/transcriptome annotations were precisely the same? What is "significant variation"? Can you show some correlation plots to support this?