Very good question. IMO, measuring expression across a 1D space is problematic – does not take into account artifacts bc of section thickness. Very sparsely 2D-cultured cells (on chip) and measuring some very well known markers, would give a good baseline. - ThreadSky

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danilexn.bsky.social • 22 days ago

Very good question. IMO, measuring expression across a 1D space is problematic – does not take into account artifacts bc of section thickness.

Very sparsely 2D-cultured cells (on chip) and measuring some very well known markers, would give a good baseline.

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danilexn.bsky.social•22 days ago

For tissues, I would trust 1D profiles if tissue is very sparse or has very large cells.

Note: lateral diffusion might happen during in-situ capture, but more important is the “diffuse background” that appears during prior steps. This actually drives most clustering artifacts.

danilexn.bsky.social•22 days ago

It depends a lot on whether one wants to measure platform- or tissue-specific differences, but also there’s a lot of readouts that can be confounded by section thickness.

danilexn.bsky.social•22 days ago

Back to the original point about clustering, some time ago there were preprints showing how to quantify and remove “diffuse” genes to improve clustering results.

I don’t share them bc I think the results were not super satisfactory. It is a completely open problem.

reinacampos.bsky.social•22 days ago

ResolVI seems to do a good job at reducing lateral diffusion artifacts in our hands… but still have not found a good metric to measure diffusion. I have seen it done by looking at RNA spillover at tissue borders, but borders are always tricky

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