Do you justify QC decisions in the supplement or just mention them in the text?
Up until now I've always worked with very clean data; I haven't had to make many hard decisions since the data looks as expected. However, I'm now working on a bit of a messy single-cell analysis that requires tough decisions. Stuff like removing a couple clusters due to high mt read % (easy to justify) but also one with inexplicably low mt read %. We also have very different library sizes, so there's some nuance to our analysis in what we can/cannot compare.
I'm usually in favour of adding too much to the supplement rather than too little. Is it typical to plot out these QC metrics in the supplement to explain why we made these decisions? Like a before and after removing poor quality clusters, or showing count distributions, etc. I see a lot of papers that just mention something like "after removing low quality cells, we..."