varExpPCA: Get optimal number of principal components
In NMikolajewicz/scMiko: scRNAseq analysis functions. Developed using Seurat framework.
View source: R/utility_functions.R
varExpPCA R Documentation
Get optimal number of principal components
Description
Get number of PCs that explain a pre-specified amount of variance.
Usage
varExpPCA(object, variance_explained = 0.9, reduction_name = "pca")
Arguments
object
Seurat object
variance_explained
proportion of variance explained. Default is 0.9.
reduction_name
name of slot with PCA reduction. default is "pca".
Value
number of PCs explaining specified amount of variance
Author(s)
Nicholas Mikolajewicz
NMikolajewicz/scMiko documentation built on June 28, 2023, 1:41 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
View source: R/utility_functions.R
| varExpPCA | R Documentation |
Get optimal number of principal components
Description
Get number of PCs that explain a pre-specified amount of variance.
Usage
varExpPCA(object, variance_explained = 0.9, reduction_name = "pca")
Arguments
object |
Seurat object |
variance_explained |
proportion of variance explained. Default is 0.9. |
reduction_name |
name of slot with PCA reduction. default is "pca". |
Value
number of PCs explaining specified amount of variance
Author(s)
Nicholas Mikolajewicz
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.