Run singular value decomposition

Run partial singular value decomposition using irlba

RunSVD(object, ...)

# Default S3 method
RunSVD(
  object,
  assay = NULL,
  n = 50,
  scale.embeddings = TRUE,
  reduction.key = "LSI_",
  scale.max = NULL,
  verbose = TRUE,
  irlba.work = n * 3,
  tol = 1e-05,
  ...
)

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

# S3 method for class 'StdAssay'
RunSVD(
  object,
  assay = NULL,
  features = NULL,
  n = 50,
  reduction.key = "LSI_",
  scale.max = NULL,
  verbose = TRUE,
  ...
)

# S3 method for class 'Seurat'
RunSVD(
  object,
  assay = NULL,
  features = NULL,
  n = 50,
  reduction.key = "LSI_",
  reduction.name = "lsi",
  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.
tol: Tolerance (tol) parameter for irlba. Larger values speed up convergence due to greater amount of allowed error.
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.
#> Warning: Requested number is larger than the number of available items (10). Setting to 10.
#> LSI_ 1 
#> Positive:  8, 6, 2, 9, 4 
#> Negative:  7, 3, 1, 10, 5 
#> Warning: Requested number is larger than the number of available items (10). Setting to 10.
#> LSI_ 2 
#> Positive:  6, 2, 10, 3, 1 
#> Negative:  4, 5, 7, 8, 9 
#> Warning: Requested number is larger than the number of available items (10). Setting to 10.
#> LSI_ 3 
#> Positive:  4, 1, 6, 8, 2 
#> Negative:  10, 5, 9, 3, 7 
#> Warning: Requested number is larger than the number of available items (10). Setting to 10.
#> LSI_ 4 
#> Positive:  2, 7, 4, 8, 9 
#> Negative:  5, 1, 6, 3, 10 
#> Warning: Requested number is larger than the number of available items (10). Setting to 10.
#> LSI_ 5 
#> Positive:  9, 2, 3, 4, 5 
#> Negative:  7, 8, 6, 10, 1 
if (FALSE) { # \dontrun{
RunSVD(atac_small[['peaks']])
} # }
if (FALSE) { # \dontrun{
RunSVD(atac_small[['peaks']])
} # }
if (FALSE) { # \dontrun{
RunSVD(atac_small)
} # }