Run a PCA dimensionality reduction. For details about stored PCA calculation
parameters, see PrintPCAParams.
RunPCA(object, pc.genes = NULL, pcs.compute = 20, use.imputed = FALSE,
rev.pca = FALSE, weight.by.var = TRUE, do.print = TRUE,
pcs.print = 1:5, genes.print = 30, ...)Seurat object
Genes to use as input for PCA. Default is object@var.genes
Total Number of PCs to compute and store
Run PCA on imputed values (FALSE by default)
By default computes the PCA on the cell x gene matrix. Setting to true will compute it on gene x cell matrix.
Weight the cell embeddings by the variance of each PC (weights the gene loadings if rev.pca is TRUE)
Print the top genes associated with high/low loadings for the PCs
PCs to print genes for
Number of genes to print for each PC
Additional arguments to be passed to IRLBA
Returns Seurat object with the PCA calculation stored in object@dr$pca.