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 DataFrames 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")
#> Mon Dec 19 18:05:25 2022 ... Running 'scran SNN clustering' with 'louvain' algorithm
#> Mon Dec 19 18:05:26 2022 ... Identified 2 clusters
#> Mon Dec 19 18:05:26 2022 ... Running TSCAN to estimate pseudotime
#> Mon Dec 19 18:05:27 2022 ... Clusters involved in path index 2 are: 1, 2
#> Mon Dec 19 18:05:27 2022 ... Number of estimated paths is 1
results <- getTSCANResults(mouseBrainSubsetSCE, "Pseudotime")