runTSCANClusterDEAnalysis | R Documentation |
This function finds all paths that root from a given cluster
useCluster
, and performs tests to identify significant features for
each path, and are not significant and/or changing in the opposite direction
in the other paths. Using a branching cluster (i.e. a node with degree > 2)
may highlight features which are responsible for the branching event. MST has
to be pre-calculated with runTSCAN
.
runTSCANClusterDEAnalysis(
inSCE,
useCluster,
useAssay = "logcounts",
fdrThreshold = 0.05
)
inSCE |
Input SingleCellExperiment object. |
useCluster |
The cluster to be regarded as the root, has to existing in
|
useAssay |
Character. The name of the assay to use. This assay should
contain log normalized counts. Default |
fdrThreshold |
Only out put DEGs with FDR value smaller than this value.
Default |
The input inSCE
with results updated in metadata
.
Nida Pervaiz
data("mouseBrainSubsetSCE", package = "singleCellTK")
mouseBrainSubsetSCE <- runTSCAN(inSCE = mouseBrainSubsetSCE,
useReducedDim = "PCA_logcounts")
mouseBrainSubsetSCE <- runTSCANClusterDEAnalysis(inSCE = mouseBrainSubsetSCE,
useCluster = 1)
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