Description Usage Arguments Value Examples
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.
1 2 3 | 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
1 2 3 4 | 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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