cellTopicHeatmap | R Documentation |
Plot cell states based on dimensionality reduction over cell-cisTopic distributions
cellTopicHeatmap(
object,
method = "Z-score",
colorBy = NULL,
colVars = NULL,
col.low = "floralwhite",
col.mid = "pink",
col.high = "red",
select.cells = NULL,
...
)
object |
Initialized cisTopic object, after the object@selected.model has been filled. |
method |
Select the normalization method to use for plotting: 'Z-score' or 'Probability'. |
colorBy |
Select the cell metadata used to colour the plots with. By default, all categorical features are used. |
colVars |
List specifying the colors to use for each label in each colouring level |
col.low |
Color to use for lowest topic enrichment |
col.mid |
Color to use for medium topic enrichment |
col.high |
Color to use for high topic enrichment |
select.cells |
If a subset of cells want to be used for making the heatmap, selected cell names can be provided (as a vector). |
... |
See |
'Z-score' computes the Z-score for each topic assingment per cell/region and 'Probability' divides the topic assignments by the total number of assignments in the cell/region in the last iteration plus alpha.
Heatmap clustering cells based on their cell-cisTopic distributions.
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