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Thank you so much for your ongoing effort to improve this package for generating beautiful plots.
Recently I have been using the Cluster_Highlight_Plot() function quite a lot to visualize my data on different embeddings and it really helped me a lot.
Initially I thought the function can only be used to generate "umap" plot because by following the code in the examples, it always returned a UMAP plot to me.
But then I realized that by specifying reduction = "other_reduction_name", it can actually be used to visualize the other embeddings as well.
Therefore, I think it would be useful to add the reduction argument to the man page of the function so that how this is used can be clarified. Meanwhile, what the default option for the reduction argument is actually not clearly stated so users may be confused by what is actually visualized without setting this in the Cluster_Highlight_Plot() function.
Hope this will help clarify the behavior of this function.
Best regards,
Jason Leong
The text was updated successfully, but these errors were encountered:
Thanks for the kind words and for submitting the issue. Yes as you found any of the parameters from Seurat::DimPlot can be passed to the function (see entry for ... in manual. However, I do agree in this case reduction should be explicitly include in the scCustomize function parameter options. I have just update this in the release dev version (v2.1.2.9070 or greater). If you have any issues after updating to that branch please let me know and I'll reopen the issue.
Dear Sam,
Thank you so much for your ongoing effort to improve this package for generating beautiful plots.
Recently I have been using the
Cluster_Highlight_Plot()
function quite a lot to visualize my data on different embeddings and it really helped me a lot.reduction = "other_reduction_name"
, it can actually be used to visualize the other embeddings as well.reduction
argument to the man page of the function so that how this is used can be clarified. Meanwhile, what the default option for thereduction
argument is actually not clearly stated so users may be confused by what is actually visualized without setting this in theCluster_Highlight_Plot()
function.Hope this will help clarify the behavior of this function.
Best regards,
Jason Leong
The text was updated successfully, but these errors were encountered: