SCTK allows user to access all TSCAN related results with
"getTSCANResults"
. See details.
getTSCANResults(x, analysisName = NULL, pathName = NULL)
# S4 method for SingleCellExperiment
getTSCANResults(x, analysisName = NULL, pathName = NULL)
getTSCANResults(x, analysisName, pathName = NULL) <- value
# S4 method for SingleCellExperiment
getTSCANResults(x, analysisName, pathName = NULL) <- value
listTSCANResults(x)
# S4 method for SingleCellExperiment
listTSCANResults(x)
listTSCANTerminalNodes(x)
# S4 method for SingleCellExperiment
listTSCANTerminalNodes(x)
Input SingleCellExperiment object.
Algorithm name implemented, should be one of
"Pseudotime"
, "DEG"
, or "ClusterDEAnalysis"
.
Sub folder name within the analysisName
. See details.
Value to be stored within the pathName
or
analysisName
Get or set TSCAN results
When analysisName = "Pseudotime"
, returns the list result from
runTSCAN
, including the MST structure.
When analysisName = "DEG"
, returns the list result from
runTSCANDEG
, including DataFrame
s containing genes that
increase/decrease along each the pseudotime paths. pathName
indicates
the path index, the available options of which can be listed by
listTSCANTerminalNodes
.
When analysisName = "ClusterDEAnalysis"
, returns the list result from
runTSCANClusterDEAnalysis
. Here pathName
needs to match
with the useCluster
argument when running the algorithm.
data("mouseBrainSubsetSCE", package = "singleCellTK")
mouseBrainSubsetSCE <- runTSCAN(inSCE = mouseBrainSubsetSCE,
useReducedDim = "PCA_logcounts")
#> Sat Mar 18 10:27:55 2023 ... Running 'scran SNN clustering' with 'louvain' algorithm
#> Sat Mar 18 10:27:55 2023 ... Identified 2 clusters
#> Sat Mar 18 10:27:55 2023 ... Running TSCAN to estimate pseudotime
#> Sat Mar 18 10:27:56 2023 ... Clusters involved in path index 2 are: 1, 2
#> Sat Mar 18 10:27:56 2023 ... Number of estimated paths is 1
results <- getTSCANResults(mouseBrainSubsetSCE, "Pseudotime")