Run runTSCAN function to obtain pseudotime values for cells

Source: R/runTSCAN.R

Wrapper for obtaining a pseudotime ordering of the cells by projecting them onto the MST

runTSCAN(inSCE, useReducedDim, cluster = NULL, seed = 12345)

Arguments

inSCE

Input SingleCellExperiment object.

useReducedDim

Character. Saved dimension reduction name in inSCE object. Required. Used for specifying which low-dimension representation to perform the clustering algorithm and building nearest neighbor graph on. Default "PCA"

cluster

Grouping for each cell in inSCE. A user may input a vector equal length to the number of the samples in inSCE, or can be retrieved from the colData slot. Default NULL.

seed

An integer. Set the seed for random process that happens only in "random" generation. Default 12345.

Value

A SingleCellExperiment object with pseudotime ordering of the cells along the paths

Author

Nida Pervaiz

Examples

data("scExample", package = "singleCellTK")
sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")
rowData(sce)$Symbol <- rowData(sce)$feature_name
rownames(sce) <- rowData(sce)$Symbol
sce <- scaterlogNormCounts(sce, assayName = "logcounts")
sce <- runDimReduce(inSCE = sce, method = "scaterPCA", 
                    useAssay = "logcounts", reducedDimName = "PCA")
#> Thu Apr 28 11:29:01 2022 ... Computing Scater PCA.
sce <- runDimReduce(inSCE = sce, method = "rTSNE", useReducedDim = "PCA", 
                    reducedDimName = "TSNE")
#> Thu Apr 28 11:29:01 2022 ... Computing RtSNE.
#> Warning: using `useReducedDim`, `run_pca` and `ntop` forced to be FALSE/NULL
sce <- runTSCAN (inSCE = sce, useReducedDim = "PCA", seed = NULL)
#> Thu Apr 28 11:29:02 2022 ... Running 'scran SNN clustering'
#> Cluster involved in path 4 are: 1:5
#> Number of estimated paths is 1