My annual reminder; if you propose doing large scale data gathering and analysis, just a *one sentence* power calculation, or "we have confidence this approach can provide robust results due to similar work of XXX in system YYY with similar sample sizes".
Why is this important in a grant? As a reviewer wont be able to fully check your power calculation (usually) but I do want to see that you are honest with *yourself* about whether the stats are going to work out. Too few samples, expected weak effects => it's never going to work
If your power calculation (which will always be pulling numbers out of the air for effect size etc; such is science) says its very unlikely you will find a credible result then... you need to reset your goals.
For me, a "technology pilot" which is framed about getting the data generation to the next level and explore sources of variance *is absolutely fine* and I prefer this to an unrealistic "and then we will associated with xx disease samples"
I appreciate some reviewers want to see the xx disease samples (not just normals, or cell lines), in which case I think the best way is to say ...
"we will also run a substantial number of disease samples to ensure the applicability of the technology to these samples, assessing variance from these samples, and we will have a reasonable chance of detecting large effects present in the disease/normal contrast".
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