Run singular value decomposition

Run partial singular value decomposition using irlba

RunSVD(object, ...)

# S3 method for default
RunSVD(
  object,
  assay = NULL,
  n = 50,
  scale.embeddings = TRUE,
  reduction.key = "SVD_",
  scale.max = NULL,
  verbose = TRUE,
  irlba.work = n + 50,
  ...
)

# S3 method for Assay
RunSVD(
  object,
  assay = NULL,
  features = NULL,
  n = 50,
  reduction.key = "SVD_",
  scale.max = NULL,
  verbose = TRUE,
  ...
)

# S3 method for Seurat
RunSVD(
  object,
  assay = NULL,
  features = NULL,
  n = 50,
  reduction.key = "SVD_",
  reduction.name = "svd",
  scale.max = NULL,
  verbose = TRUE,
  ...
)

Arguments

object	A Seurat object
...	Arguments passed to other methods
assay	Which assay to use. If NULL, use the default assay
n	Number of singular values to compute
scale.embeddings	Scale cell embeddings within each component to mean 0 and SD 1 (default TRUE).
reduction.key	Key for dimension reduction object
scale.max	Clipping value for cell embeddings. Default (NULL) is no clipping.
verbose	Print messages
irlba.work	work parameter for irlba. Working subspace dimension, larger values can speed convergence at the cost of more memory use.
features	Which features to use. If NULL, use variable features
reduction.name	Name for stored dimension reduction object. Default 'svd'

Value

Returns a Seurat object

Examples

x <- matrix(data = rnorm(100), ncol = 10)
RunSVD(x)
#> Running SVD
#> Warning: You're computing too large a percentage of total singular values, use a standard svd instead.
#> Scaling cell embeddings
#> Warning: No assay specified, setting assay as RNA by default.
#> A dimensional reduction object with key SVD_ 
#>  Number of dimensions: 9 
#>  Projected dimensional reduction calculated:  FALSE 
#>  Jackstraw run: FALSE 
#>  Computed using assay: RNA 
RunSVD(atac_small[['peaks']])
#> Running SVD
#> Warning: You're computing too large a percentage of total singular values, use a standard svd instead.
#> Scaling cell embeddings
#> Warning: No assay specified, setting assay as RNA by default.
#> A dimensional reduction object with key SVD_ 
#>  Number of dimensions: 50 
#>  Projected dimensional reduction calculated:  FALSE 
#>  Jackstraw run: FALSE 
#>  Computed using assay: RNA 
RunSVD(atac_small)
#> Running SVD
#> Warning: You're computing too large a percentage of total singular values, use a standard svd instead.
#> Scaling cell embeddings
#> An object of class Seurat 
#> 300 features across 100 samples within 3 assays 
#> Active assay: peaks (100 features, 90 variable features)
#>  2 other assays present: bins, RNA
#>  3 dimensional reductions calculated: lsi, umap, svd