For example, I have datasets of two groups - healthy and disease

Total 10 samples in each group

Datasets mix from different studies (so there must be batch effects)

I want to run analysis

First, lets say soupX

Then Doublet Finder

Then seurat workflow with Harmony integration

Annotate Clusters

Subset subtype

At each levels, I have to run steps which requires fine tuning at sample level.

For example, resolution, dims, expected fraction of doublets (which needs to be set, based on recovered cell numbers, 10x documentation).

How should I do?

1. Should I specify such for each samples Or
2. Should I proceed with a function with fixed but okayish type value for all samples (like 0.7 resolution or 0.045 if i have 4000 to 10000 recovered cells). Is this a non-problematic way?

Although sample level fine tuning should be the best way to do, I want to know if group level (batch or condition) tuning is a good approach. Global level tuning is not suitable at all (one fixed function for all samples be it coming from any batch, condition, samples).

Thanks you!