Create heatmap for showing top marker expression in conditions
Source:R/DEG_marker.R
plotMarkerHeatmap.Rd
Create heatmap for showing top marker expression in conditions
Usage
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,
...
)
Arguments
- object
A liger object, with normalized data and metadata to annotate available.
- result
The data.frame returned by
runMarkerDEG
.- topN
Number of top features to be plot for each group. Default
5
.- lfcThresh
Hard threshold on logFC value. Default
1
.- padjThresh
Hard threshold on adjusted P-value. Default
0.05
.- pctInThresh, pctOutThresh
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 forpctOutThresh
. Default50
percent for both.- dedupBy
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"
.- groupBy
Cell metadata variable names for cell grouping. Downsample balancing will also be aware of this. Default
c("dataset", "leiden_cluster")
.- groupSize
Maximum number of cells in each group to be downsampled for plotting. Default
50
.- column_title
Title on the column. Default
NULL
.- ...
Parameter passed to wrapped functions in the inheritance order:
plotGeneHeatmap
,.plotHeatmap
,ComplexHeatmap::Heatmap
Examples
markerTable <- runMarkerDEG(pbmcPlot)
#> ℹ Running Wilcoxon rank-sum test
#> ✔ Running Wilcoxon rank-sum test ... done
#>
plotMarkerHeatmap(pbmcPlot, markerTable)
#> ℹ Subsetting dataset: "ctrl"
#> ℹ Subsetting dataset: "stim"
#> ✔ Subsetting dataset: "stim" ... done
#>
#> ℹ Subsetting dataset: "ctrl"
#> ✔ Subsetting dataset: "ctrl" ... done
#>