rliger: optimizeNewK – R documentation

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optimizeNewK

Perform factorization for new value of k

Description

This uses an efficient strategy for updating that takes advantage of the information in the existing factorization. It is most recommended for values of k smaller than current value, where it is more likely to speed up the factorization.

Usage

optimizeNewK(
  object,
  k.new,
  lambda = NULL,
  thresh = 1e-04,
  max.iters = 100,
  rand.seed = 1,
  verbose = TRUE
)

Arguments

`object`	`liger` object. Should call optimizeALS before calling.
`k.new`	Inner dimension of factorization (number of factors)
`lambda`	Regularization parameter. By default, this will use the lambda last used with optimizeALS.
`thresh`	Convergence threshold. Convergence occurs when \|obj0-obj\|/(mean(obj0,obj)) < thresh (default 1e-4).
`max.iters`	Maximum number of block coordinate descent iterations to perform (default 100).
`rand.seed`	Random seed to set. Only relevant if k.new > k. (default 1)
`verbose`	Print progress bar/messages (TRUE by default)

Value

liger object with H, W, and V slots reset.

Examples

## Not run: 
# decide to run with k = 15 instead (keeping old lambda the same)
ligerex <- optimizeNewK(ligerex, k.new = 15)

## End(Not run)

rliger

Linked Inference of Genomic Experimental Relationships

v1.0.0

GPL-3

Authors

Joshua Welch [aut, ctb], Chao Gao [aut, ctb, cre], Jialin Liu [aut, ctb], Joshua Sodicoff [aut, ctb], Velina Kozareva [aut, ctb], Evan Macosko [aut, ctb], Paul Hoffman [ctb], Ilya Korsunsky [ctb], Robert Lee [ctb]

Initial release

2021-04-18