View source: R/dimensional_reduction.R
ProjectDim | R Documentation |
Takes a pre-computed dimensional reduction (typically calculated on a subset of genes) and projects this onto the entire dataset (all genes). Note that the cell loadings will remain unchanged, but now there are gene loadings for all genes.
ProjectDim(
object,
reduction = "pca",
assay = NULL,
dims.print = 1:5,
nfeatures.print = 20,
overwrite = FALSE,
do.center = FALSE,
verbose = TRUE
)
object |
Seurat object |
reduction |
Reduction to use |
assay |
Assay to use |
dims.print |
Number of dims to print features for |
nfeatures.print |
Number of features with highest/lowest loadings to print for each dimension |
overwrite |
Replace the existing data in feature.loadings |
do.center |
Center the dataset prior to projection (should be set to TRUE) |
verbose |
Print top genes associated with the projected dimensions |
Returns Seurat object with the projected values
data("pbmc_small")
pbmc_small
pbmc_small <- ProjectDim(object = pbmc_small, reduction = "pca")
# Vizualize top projected genes in heatmap
DimHeatmap(object = pbmc_small, reduction = "pca", dims = 1, balanced = TRUE)
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