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(feat): match pbmc3k tutorial to seurat's #171

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@ilan-gold ilan-gold commented May 6, 2025

TODO:

  • Figure out best way for ranking genes so that we recover meaningful results. At the moment, running the method on the full gene list yields a lot of RP genes for the CD4 cluster ,which I would guess is basically noise. But it seems that seurat uses the full list. Separately I can't seem to figure out how to get the scores from seurat - they are claimed to be present but I don't seem them. I don't think they are just lfc.
  • Marker gene documentation CD8A and CD8B are not present in the ranked genes either here or in seurat but are noted as marker genes. So I think we should just change that table and note that some genes are not present the ranked genes (maybe explain why? talk to Rahul again?)
  • PCA Rahul's PCA is quite similar but not exact. It would be nice maybe for them to have arpack since an R implementation exists: https://search.r-project.org/CRAN/refmans/igraph/html/arpack.html and
  • Clustering Same as above, especially since igraph is available in R: https://igraph.org/r/doc/cluster_leiden.html

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@ilan-gold ilan-gold force-pushed the ig/seruat_compat branch from 776f7f5 to 7629596 Compare May 7, 2025 12:50
@ilan-gold ilan-gold requested a review from flying-sheep May 7, 2025 12:50
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ilan-gold commented May 7, 2025

@flying-sheep Still very rough, but looking for some feedback given the above "outstanding" issues, especially on framing the reproducibility aspect

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flying-sheep commented May 8, 2025

Blast from the past: I also use an ARPACKy PCA in destiny, using RSpectra:

If nothing changed in the space, that might be their way forward as well, but of course I don’t know if RSpectra’s PCA is 100% identical to ARPACK.

@flying-sheep flying-sheep linked an issue May 15, 2025 that may be closed by this pull request
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flying-sheep commented on 2025-05-15T15:26:26Z
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there seems to be no output from print_header


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flying-sheep commented on 2025-05-15T15:26:27Z
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I don’t really get what “up to ties” means


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flying-sheep commented on 2025-05-15T15:26:28Z
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Line #2.    adata_subset_hvg = adata[:, adata.var["highly_variable"]].copy()

hmm, maybe explain that you’re using that subset for a while until you go back to the non-subset one?

I think it’s maybe a bit confusing that there are two adata objects being used interspersedly. I think modifying a notebook like that can easily result in copy-pasting the wrong name.

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flying-sheep commented on 2025-05-15T15:26:28Z
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We should just switch to sc.tl.marker_gene_overlap instead of changing these around everytime this file is touched.


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(bug): pbmc3k tutorial is not reproducible
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