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RunALRA() implements the ALRA imputation algorithm. It computes a rank-k approximation of the normalized expression matrix, then adaptively thresholds values based on the distribution of negative values in the approximation. Zero values are preserved only when they are truly absent.

​
Syntax

RunALRA(
  object,
  k = NULL,
  q = 10,
  quantile.prob = 0.001,
  use.mkl = FALSE,
  mkl.seed = -1,
  assay = NULL,
  slot = "data",
  setDefaultAssay = TRUE,
  genes.use = NULL,
  K = NULL,
  p.val.th = 1e-10,
  noise.start = NULL,
  q.k = 2,
  k.only = FALSE,
  ...
)

​
Parameters

​
object
Seurat
required
A Seurat object. Also accepts a matrix-like object when called as a default method.
​
k
integer
default:"NULL"
Rank of the low-rank approximation. Set to NULL for automated selection of k.
​
q
integer
default:"10"
Number of additional power iterations in randomized SVD when computing the rank-k approximation.
​
quantile.prob
numeric
default:"0.001"
Quantile probability used to calculate the per-gene threshold.
​
use.mkl
logical
default:"FALSE"
Use the Intel MKL-based SVD implementation (requires rpca-mkl package).
​
mkl.seed
integer
default:"-1"
Seed for the MKL SVD random generator. Any negative value uses the current timestamp. Only relevant when use.mkl = TRUE.
​
assay
character
default:"NULL"
Name of the assay to use. Defaults to the active default assay.
​
slot
character
default:"data"
Slot within the assay to use as input.
​
setDefaultAssay
logical
default:"TRUE"
If TRUE, sets the resulting alra assay as the default assay after imputation.
​
genes.use
character vector
default:"NULL"
Subset of genes to impute. Defaults to all genes in the assay.
​
K
integer
default:"NULL"
Number of singular values to compute when choosing k automatically. Must be less than the smallest matrix dimension. Defaults to 100 or the smallest dimension, whichever is less.
​
p.val.th
numeric
default:"1e-10"
P-value threshold for significance when choosing k automatically.
​
noise.start
integer
default:"NULL"
Index from which all smaller singular values are considered noise during automatic k selection. Defaults to K - 20.
​
q.k
integer
default:"2"
Number of additional power iterations when choosing k automatically.
​
k.only
logical
default:"FALSE"
If TRUE, computes the optimal k and stores it in the object without performing imputation. Use with ALRAChooseKPlot() to visualize the choice.

​
Returns

A Seurat object with a new assay named alra containing the imputed expression matrix. When setDefaultAssay = TRUE, this becomes the default assay. When k.only = TRUE, returns the object with the computed k stored in the tool slot.

​
Examples

library(SeuratWrappers)

# Simple one-step imputation
pbmc_small <- RunALRA(object = pbmc_small)

# Two-step: choose k first, then impute
pbmc_alra <- RunALRA(pbmc_small, k.only = TRUE)
ggouts <- ALRAChooseKPlot(pbmc_alra)
do.call(gridExtra::grid.arrange, c(ggouts, nrow = 1))
pbmc_alra <- RunALRA(pbmc_alra)

​
See Also

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