Comments (2)
Hi,
The reference data set is chosen based on the 'reference.data' argument to scAlignMulti()
. Assuming the list of SCE objects is named before calling scAlignCreateObject()
then setting reference.data to one of those names will specify the reference set, otherwise all-pairs alignment is performed.
We haven't tried SCTransform as a normalization method but using the residuals from SCTransform should work as well if not better than the results of ScaleData.
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Alright that worked.
Also the tutorials for multiway alignment has an error in it, I believe. When your extracting the common set of variable genes across datasets, and then pull those rows to create the SCE object it throws on out of bounds error. I fixed this by intersecting the union with all genes in all batches.
Thanks.
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Related Issues (10)
- ImportError: No module named tensorflow , when installing scAlign HOT 5
- Feature request: per batch l2-normalization at embedding generation for training on large datasets HOT 3
- Question about the loss? HOT 2
- scAlign_supervised_alignment example: "Error during alignment, returning scAlign class." HOT 1
- Running Issues
- Error during interpolation, returning scAlign class. HOT 9
- Setting up differential expression with multiway alignment HOT 16
- tensorflow error HOT 3
- MultiCCA parameter HOT 1
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