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Hi,
I am running ascend with the following commands:
em <- ascend::newEMSet(assays = list(counts = data))
em <- ascend::filterLowAbundanceGenes(em)
em <- ascend::normaliseByRLE(em)
em <- ascend::runPCA(em)
em <- ascend::runCORE(em, nres=40)
In some of my datasets after runCORE is performed I see less number of cells stored in em object. It seems ascend removes some cells when performing clustering. Is it something normal, in the sense that the low quality cells are removed or it can be related to some errors in the clustering function?
I would be grateful for your help,
Monika
The text was updated successfully, but these errors were encountered:
Hi Monika,
runCORE removes cells that are not assigned to any cluster (i.e. singleton cells) and iteratively performs this scanning for outliers five times until no singleton is found or a message will be shown: "Many outliers have been detected. Please review your filtering and normalisation methods before trying to cluster again."
We will edit the function documentation to clarify this default step.
Best wishes,
Quan
Hi,
I am running ascend with the following commands:
em <- ascend::newEMSet(assays = list(counts = data))
em <- ascend::filterLowAbundanceGenes(em)
em <- ascend::normaliseByRLE(em)
em <- ascend::runPCA(em)
em <- ascend::runCORE(em, nres=40)
In some of my datasets after runCORE is performed I see less number of cells stored in em object. It seems ascend removes some cells when performing clustering. Is it something normal, in the sense that the low quality cells are removed or it can be related to some errors in the clustering function?
I would be grateful for your help,
Monika
The text was updated successfully, but these errors were encountered: