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Improvements for Stereoseq reader #97
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Thank you @florianingelfinger for the feedback, and indeed great work from @LLehner @timtreis and Maiia! 🎉 If you cold open a pull request for point 1 it would be convenient for us, but anyway we will try to incorporate the feedback before merging the stereoseq PR to main. Regarding the points 3 and 4, I kindly ask you if you could create a reproducible example with artificial data and open an issue in I am happy to work on point 3 but currently I don't have stereoseq data on my machine, and it could be the same for point 4 for which @Sonja-Stockhaus could help. Thank you, |
Chiming in for #4, I just released a version to pypi with a bunch of fixes. Could you try and see if the issue persists? |
I will begin shortly with adding 1. and 2. to the reader. |
Points 1. and 2. have been added to the reader and there is a significant speed-up. Try How is it going with the rest? |
@LLehner: quick feedback to the update. I am getting an error in l 108 of the stereoseq reader because the .gef file does not exist in the register folder anymore. I think l 107 should also use |
Oh, missed that line before. Should work now though. |
Additionally, there seems a problem with the naming of the image, shapes and labels keys. The element names must be unique but the images keys and the labels keys are the same (the image file name of the *_mask.tif file). We can also have a quick call to look into it together next week if more convenient for you? |
Hi guys,
many thanks for the great package and especially Laurens, Tim and Maiia for enabling the Stereoseq support within spatialdata. I just had a call with Laurens and he suggested to document potential improvements for the stereoseq reader in this issue.
The following suggestions refer to Laurens pull request #70
StereoseqKeys.CELLCUT
rather thanStereoseqKeys.REGISTER
StereoseqKeys.REGISTER
folder that start with either 'DAPI' or 'ssDNA'*_fov_stitched_transformed.tif
are not used in any downstream analysis task and are untransformed replicates ofregist.tif
I would kick these out.I am not sure whether this is a user error but I think there may be a problem with reading the segmentation mask. E.g. when aggregating image intensities over the segmentation mask (according to your vignette https://spatialdata.scverse.org/en/latest/tutorials/notebooks/notebooks/examples/aggregation.html) I obtain a single
.obs
in the table slot. Is there a reason to not incorporate the cell boundaries (as specified in the.obsm
) as shapes?Also not sure if a user error or related to 3). Rendering shapes with color keys from the table slot results in grey images and color keys are not correctly displayed.
E.g.
sdata.pl.render_shapes(color="total_counts").pl.show()
does not display the total counts which is an.obs
columns in the table slot of sdata. Do you have any idea what I may cause this issue?Many thanks for the great community work. Let me know if you would prefer a pull request for 1).
Cheers,
Flo
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