RunMCTSNE {CelliD} | R Documentation |
(!EXPERIMENTAL) Run TSNE on MCA fetures and cells coordinates This will allow to embbed in 2D both cells and the genes at the same time.
RunMCTSNE(X, reduction, dims, features, reduction.name, ...) ## S3 method for class 'Seurat' RunMCTSNE( X, reduction = "mca", dims = seq(50), features = NULL, reduction.name = "mctsne", assay = DefaultAssay(X), ... ) ## S3 method for class 'SingleCellExperiment' RunMCTSNE( X, reduction = "MCA", dims = seq(50), features = NULL, reduction.name = "MCTSNE", ... )
X |
Seurat or SingleCellExperiment object |
reduction |
Which dimensionality reduction to use, must be based on MCA. |
dims |
A vector of integers indicating which dimensions to use with reduction embeddings and loadings for distance calculation. |
features |
Character vector of feature names to subset feature coordinates. If not specified will take all features available from specified reduction Loadings. |
reduction.name |
name of the created dimensionlaity reduction, default set to "mca" for Seurat and "MCA" for SCE. |
... |
other arguments passed to methods or Rtsne::Rtsne |
assay |
Seurat assay slot. When not specified set with DefaultAssay(X) |
Seurat or SingleCellExperiment object with MCTSNE stored in the reduction slot
seuratPbmc <- RunMCA(seuratPbmc, nmcs = 5) seuratPbmc <- RunMCTSNE(seuratPbmc, dims = seq(5))