Create heatmap for showing top marker expression in conditions
plotMarkerHeatmap(
object,
result,
topN = 5,
lfcThresh = 1,
padjThresh = 0.05,
pctInThresh = 50,
pctOutThresh = 50,
dedupBy = c("logFC", "padj"),
groupBy = NULL,
groupSize = 50,
column_title = NULL,
...
)
A liger object, with normalized data and metadata to annotate available.
The data.frame returned by runMarkerDEG
.
Number of top features to be plot for each group. Default
5
.
Hard threshold on logFC value. Default 1
.
Hard threshold on adjusted P-value. Default 0.05
.
Threshold on expression percentage. These
mean that a feature will only pass the filter if it is expressed in more than
pctInThresh
percent of cells in the corresponding cluster. Similarly
for pctOutThresh
. Default 50
percent for both.
When ranking by padj and logFC and a feature is ranked as top
for multiple clusters, assign this feature as the marker of a cluster when
it has the largest "logFC"
in the cluster or has the lowest
"padj"
. Default "logFC"
.
Cell metadata variable names for cell grouping. Downsample
balancing will also be aware of this. Default c("dataset",
"leiden_cluster")
.
Maximum number of cells in each group to be downsampled for
plotting. Default 50
.
Title on the column. Default NULL
.
Parameter passed to wrapped functions in the inheritance order:
plotGeneHeatmap
, .plotHeatmap
,
ComplexHeatmap::Heatmap
markerTable <- runMarkerDEG(pbmcPlot)
plotMarkerHeatmap(pbmcPlot, markerTable)
Run the code above in your browser using DataLab