Quentin Blampey

Results 233 comments of Quentin Blampey

I'm talking about the `images` directory of the MERSCOPE output, it's not related to Sopa or AnnData. That is, the data directory that you provide to Sopa, not the output...

Hi @pakiessling, Thanks for sending these detailed images. It seems the segmentation here is pretty difficult (is it DAPI staining?), so I think the results are less consistent than expected...

In `sopa==2.1.0`, there is a `no_overlap` argument in [sopa.aggregate](https://gustaveroussy.github.io/sopa/api/aggregation/#sopa.aggregate), please let me know if it helps @pakiessling!

Hello @AdritaSaha, Which technology do you have? If you have Xenium data, I recommend using the Xenium Explorer to align them, as described [in this tutorial](https://gustaveroussy.github.io/sopa/tutorials/align/). Else, you can do...

Hi @AdritaSaha, if you used the Xenium Explorer for the alignment, you can normally already see your aligned H&E image. Still, afterward, you can use [napari-spatialdata](https://github.com/scverse/napari-spatialdata) (interactive) or [spatialdata-plot](https://github.com/scverse/spatialdata-plot) (static)...

Thanks for the clarification. Could you show me the structure of your `SpatialData` object so that I can understand better what's inside? And when you say that you segmented your...

Thanks @stergioc! I'll do some tests on my side The plots are really weird indeed, and I don't think that the stripe effect is related to plotting. Could it be...

Looking better indeed @stergioc! The scaling issue is indeed concerning here... It may be due to this [known issue](https://github.com/scverse/spatialdata-plot/issues/216), but here the shift is huge, so I'm afraid there is...

I ran your code and was able to reproduce the issue: I had a look to the patches, but they look good: ```python >>> slide["embeddings_patches"].attrs {'transform': {'global': Scale (x, y)...

Actually, if I plot the shapes only: ```python slide.pl.render_shapes("embeddings_patches", color="cluster", fill_alpha=0.5).pl.show() ``` I get this: I was assuming the shapes were cut in the previous plot, but actually not! Suggesting...