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I am running SEACells on a dataset of sc-ATAC-seq of 31000 cells and I am inferring 310 cells.
When checking for quality of results, I am surprised at the amount of cells that have 0 non-trivial assignment. Is this normal? Is there a way I can maximise the amount of cells having at least one SEACell assigned?
This is the plot I get:
Thank you.
The text was updated successfully, but these errors were encountered:
This is quite likely a result of specifying too many metacells. We do recommend the use of one metacell for 75-80 single-cells, but this is a function of the complexity of the single-cell data. We would recommend in this case to perhaps use 150 metacells to see if it helps improve the results. A visual check on umap/visualization of your choice can also serve as a reasonable QC check.
Hello,
I am running SEACells on a dataset of sc-ATAC-seq of 31000 cells and I am inferring 310 cells.
When checking for quality of results, I am surprised at the amount of cells that have 0 non-trivial assignment. Is this normal? Is there a way I can maximise the amount of cells having at least one SEACell assigned?
This is the plot I get:
Thank you.
The text was updated successfully, but these errors were encountered: