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I realized the input to dimensional reduction for X and Z0 only contain a selected number of genes (highly variable in both RNA and gene activity score calculated from scATAC cells) and the subsequent gene expression imputation was also just on these 'gene.use' genes. If I want to impute the all transcriptome, could I modify the imputeZ like this to impute the all genes present in the original rna dataset for the scATAC cell? (see below)
code:
impuZ(X=rna[["RNA"]], bicca = res) # even though the BiCCA was run using reduced dimensions calculated from 'gene.use' genes.
Would greatly appreciate your thoughts on this. Thank you!
Best regards,
Michelle
The text was updated successfully, but these errors were encountered:
Hi bindSC team,
Thanks for the great package.
I'm following the mouse retina tutorial .
I realized the input to dimensional reduction for X and Z0 only contain a selected number of genes (highly variable in both RNA and gene activity score calculated from scATAC cells) and the subsequent gene expression imputation was also just on these 'gene.use' genes. If I want to impute the all transcriptome, could I modify the imputeZ like this to impute the all genes present in the original rna dataset for the scATAC cell? (see below)
code:
impuZ(X=rna[["RNA"]], bicca = res) # even though the BiCCA was run using reduced dimensions calculated from 'gene.use' genes.
Would greatly appreciate your thoughts on this. Thank you!
Best regards,
Michelle
The text was updated successfully, but these errors were encountered: