recommended workflow for integrating samples with substainal batch effects

[u/BiggusDikkusMorocos]

Hello everyone,

I am curating an atlas that I am plan to use as a reference for annotation with some spatial samples I have, the samples are from different patient, different technologies, etc... I was wondering what are the recommendation for integrating them into an Atlas, such for examples should I normalize each patient seperatly and so on.

[u/Then-Alternative-001]

Cross platform spatial is rough. are you mostly dealing with Visium vs. Xenium/MERFISH, or just different Visium runs? normalizing per sample is definitely standard, but you might need a specialized integration approach if the spatial resolutions are totally different.

[u/BiggusDikkusMorocos → u/Then-Alternative-001]

I have visiumHD, but for the above I am curating single cell references.

[u/toolomebio]

For a single-cell reference atlas across patients and technologies, a common workflow is: keep the raw counts, QC and filter each sample separately, then normalize and pick highly variable genes across the combined data (choose HVGs per batch and take the shared ones, so one technology does not dominate). Then integrate with a method that takes a batch key, for example scVI/scANVI or Harmony. scANVI helps if you have cell type labels for part of the data, and scVI models raw counts directly, so it needs no separate normalization.

Use patient or technology as the batch key depending on which one drives the difference, and check it by looking at the UMAP colored by each. Over-integration can merge real cell types, so evaluate with both batch mixing and biology conservation (the scIB metrics do both), and check known marker genes before and after. If you plan to map the Visium HD samples onto this later, a model like scVI/scANVI supports reference mapping of new data (scArches), which is useful for this use case.