Do we need to correct the batch effects of given datasets

[HelloWorldLTY]

Hi, thanks for your great work. I wonder if we need to correct the batch effects of these spatial transcriptomic data or not. Thanks a lot!

[guillaumejaume]

Hi, it depends on what you want to do with HEST data. What's your use case?

[HelloWorldLTY]

I am interested in the Visium data only. Thanks.

[guillaumejaume]

Visium data integrated into HEST-1k are very diverse: 2 species (mouse and human), multiple diseases, and organs. Batch effect correction should always be done if there are some guarantees that it won't significantly alter the biological signal.

To give a better answer, I need a better understanding of your problem statement, e.g., multimodal representation learning, ST prediction from H&E, characterization of morphological correlates of expression changes, etc.

If you want to explore batch effect, we implemented 2 core functions:

• Batch effect visualization, here, which does a UMAP viz of the gene expression of housekeeping genes (ie stable genes) in the stromal region. The function can take as input a series of visium samples that you want to use.
• Batch effect correction, here, which can correct batch effects using MNN, Harmony, and Combat. The output of each method is different, e.g., Harmony creates a new latent space, so the output cannot be interpreted as gene counts anymore (this may or may not be an issue for your problem statement)

[HelloWorldLTY]

Thanks! I will take a look at it!

[guillaumejaume]

@HelloWorldLTY, feel free to document any findings on this GitHub issue.