Description Usage Arguments Value
Run a PCA dimensionality reduction. For details about stored PCA calculation
parameters, see PrintPCAParams
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | RunPCA(object, ...)
## Default S3 method:
RunPCA(object, assay = NULL, npcs = 50,
rev.pca = FALSE, weight.by.var = TRUE, verbose = TRUE,
ndims.print = 1:5, nfeatures.print = 30, reduction.key = "PC_",
seed.use = 42, approx = TRUE, ...)
## S3 method for class 'Assay'
RunPCA(object, assay = NULL, features = NULL,
npcs = 50, rev.pca = FALSE, weight.by.var = TRUE, verbose = TRUE,
ndims.print = 1:5, nfeatures.print = 30, reduction.key = "PC_",
seed.use = 42, ...)
## S3 method for class 'Seurat'
RunPCA(object, assay = NULL, features = NULL,
npcs = 50, rev.pca = FALSE, weight.by.var = TRUE, verbose = TRUE,
ndims.print = 1:5, nfeatures.print = 30, reduction.name = "pca",
reduction.key = "PC_", seed.use = 42, ...)
|
object |
An object |
... |
Arguments passed to other methods and IRLBA |
assay |
Name of Assay PCA is being run on |
npcs |
Total Number of PCs to compute and store (50 by default) |
rev.pca |
By default computes the PCA on the cell x gene matrix. Setting to true will compute it on gene x cell matrix. |
weight.by.var |
Weight the cell embeddings by the variance of each PC (weights the gene loadings if rev.pca is TRUE) |
verbose |
Print the top genes associated with high/low loadings for the PCs |
ndims.print |
PCs to print genes for |
nfeatures.print |
Number of genes to print for each PC |
reduction.key |
dimensional reduction key, specifies the string before the number for the dimension names. PC by default |
seed.use |
Set a random seed. By default, sets the seed to 42. Setting NULL will not set a seed. |
approx |
Use truncated singular value decomposition to approximate PCA |
features |
Features to compute PCA on |
reduction.name |
dimensional reduction name, pca by default |
Returns Seurat object with the PCA calculation stored in the reductions slot
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.