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Hi there,
Thanks for a great tool.
tidyseurat::aggregate_cells only pull some but not all metadata columns of the original Seurat object.
tidyseurat::aggregate_cells
Would you mind taking a look?
Thank you again.
seuratObj %>% tidyseurat::aggregate_cells(.sample = c(Leiden39PCRes1p2_clusterID_2024Jan09), assays = "SCT", slot = "data", aggregation_function=Matrix::rowSums) |> filter(.feature %in% gene_vector) -> seuratObj_Data
> ncol(seuratObj_Data) [1] 25 > ncol([email protected]) [1] 92
The text was updated successfully, but these errors were encountered:
Hello,
Only metadata columns relative to samples and features are pulled. the ones about cells do not fit bulk data anymore.
@william-hutchison could you please add a message to the aggregate_cells of tidyseurat and tidySCE communicating this?
Only for tidyseurat also add a second message that says that you can then use tidySE to convert to SE with the code ..
Please @denvercal1234GitHub confirm that such message is very understandable by you. Otherwise please propose an alternative.
Sorry, something went wrong.
The comment that tidyseurat::aggregate_cells only pull sample-level and feature-level metadata columns but not cell-level columns" makes sense.
But, I am confused about the conversion to SE using tidySE? What is it for?
tidySE
Thank you both.
actually is tidybulk::as_SummarizedExperiment
you want SE if you do bulk analyses for example. many tools including tidybulk accept SE
I see. tidybulk is to analyze bulk-RNAseq data and not scRNAseq data.
tidybulk
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Hi there,
Thanks for a great tool.
tidyseurat::aggregate_cells
only pull some but not all metadata columns of the original Seurat object.Would you mind taking a look?
Thank you again.
The text was updated successfully, but these errors were encountered: