Comments (2)
Hello Francesco,
perhaps you can visualize the UCell scores alongside the expression of individual genes: e.g.
FeaturePlot(CD8sub, c("CD8_UCell", "CD4_UCell")
This may help you identify better thresholds for filtering. One thing to keep in mind is that UCell scores are smoothed by their nearest neighbors, so even if a cell has low score for a given signature, but most of its neighbors are high, it may still pass through the filter (and the opposite).
It's true that there seems to be a cluster of CD8A- cells in your plots. One thing to check: how many genes are detected in your dataset (and in this cluster in particular)? By default UCell scores are calculated on the top ranking 1500 genes per cell, but if you have fewer than this number of detected genes, even lowly expressed genes may get non-zero scores. You could try to lower the maxRank
parameter which controls this behavior.
Finally, the CD4 gene is often not very well detected in scRNA-seq. You may be able to increase the sensitivity of the gating model by adding some other genes to the CD4 signature. For instance we found CD40LG to be useful to purify CD4+ T cells, in combination with CD4.
I hope this helps,
-massimo
from scgate.
Thank you Massimo.
I'll give it a try!!
Best,
Francesco
from scgate.
Related Issues (20)
- new function to evaluate multiple models (list) with one command HOT 1
- new function to obtain a multi-class variable from a set of scGate models' pure/impure output HOT 3
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- Ucell scores for _additional_signatures_ not exported in multi-model mode [dev]
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- scGate & performance.metrics HOT 3
- nn.idx with pre-calculated dimensionality reductions HOT 5
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- combining model_DBs HOT 6
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- Create model for macrophages HOT 1
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