Comments (3)
Hi @Winnie09, we use the normalize_data()
function to convert the count matrix into a library size and log transformed matrix. We have not explored the effects of not normalizing or not doing the log transform, however.
The output can be considered to have the same "transformation" done to it as the input data. The alra()
function itself does not actually do any normalization, but if the input data was normalized, then the imputed data will have roughly the same distribution.
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Hi @linqiaozhi I have a quick question related to this one:
Would you recommend applying ALRA to impute scaled data or raw data in the count matrix?
Thank you so much for the question and the software.
FYI, I'm applying this on scRNA Seq data being analyzed on Seurat.
Regards,
Deep
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Related Issues (20)
- Best Practice for imputing big data-sets HOT 2
- Can I use ALRA imputed matrix to perform the `Find Marker Gene` step ? HOT 2
- Tips for larger matrices? HOT 3
- During FindVariableFeatures after ALRA output, count slot is empty?
- Error in asMethod(object)
- GetAssayData(pbmc, slot = "counts") gives 0 x 0 matrix HOT 1
- Run ALRA in Seurat v4.1.0
- Imputation before other QC steps?
- ALRA and Seurat HOT 1
- Need to deal with R 4.2.0 HOT 5
- alraSeurat2 FUNCTION NOT FOUND!!!! HOT 3
- Final proportion of non-zero values is large. HOT 2
- Running ALRA with multiple samples HOT 10
- Differential expression HOT 5
- Provided normalized function HOT 4
- Imputing integrated data HOT 1
- Input data structure HOT 1
- big data set and K HOT 2
- Input format (genes as rows?) HOT 1
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