wrapper.dapar.impute.mi: Missing values imputation using the LSimpute algorithm.

In samWieczorek/DAPAR: Tools for the Differential Analysis of Proteins Abundance with R

Missing values imputation using the LSimpute algorithm.

Description

This method is a wrapper to the function impute.mi of the package imp4p adapted to an object of class MSnSet.

Usage

wrapper.dapar.impute.mi(
  obj,
  nb.iter = 3,
  nknn = 15,
  selec = 600,
  siz = 500,
  weight = 1,
  ind.comp = 1,
  progress.bar = FALSE,
  x.step.mod = 300,
  x.step.pi = 300,
  nb.rei = 100,
  method = 4,
  gridsize = 300,
  q = 0.95,
  q.min = 0,
  q.norm = 3,
  eps = 0,
  methodi = "slsa",
  lapala = TRUE,
  distribution = "unif"
)

Arguments

obj	An object of class MSnSet.
nb.iter	Same as the function mi.mix in the package imp4p
nknn	Same as the function mi.mix in the package imp4p
selec	Same as the function mi.mix in the package imp4p
siz	Same as the function mi.mix in the package imp4p
weight	Same as the function mi.mix in the package imp4p
ind.comp	Same as the function mi.mix in the package imp4p
progress.bar	Same as the function mi.mix in the package imp4p
x.step.mod	Same as the function estim.mix in the package imp4p
x.step.pi	Same as the function estim.mix in the package imp4p
nb.rei	Same as the function estim.mix in the package imp4p
method	Same as the function estim.mix in the package imp4p
gridsize	Same as the function estim.mix in the package imp4p
q	Same as the function mi.mix in the package imp4p
q.min	Same as the function impute.pa in the package imp4p
q.norm	Same as the function impute.pa in the package imp4p
eps	Same as the function impute.pa in the package imp4p
methodi	Same as the function mi.mix in the package imp4p
lapala	xxxxxxxxxxx
distribution	The type of distribution used. Values are unif (default) or beta.

Value

The Biobase::exprs(obj) matrix with imputed values instead of missing values.

Author(s)

Samuel Wieczorek

Examples

## Not run: 
utils::data(Exp1_R25_pept, package='DAPARdata')
obj <- Exp1_R25_pept[1:100]
level <- obj@experimentData@other$typeOfData
metacell.mask <- match.metacell(GetMetacell(obj), 'missing', level)
indices <- GetIndices_WholeMatrix(metacell.mask, op='>=', th=1)
obj.imp.na <- wrapper.dapar.impute.mi(obj, nb.iter=1, lapala = TRUE)
obj.imp.pov <- wrapper.dapar.impute.mi(obj, nb.iter=1, lapala = FALSE)

## End(Not run)

samWieczorek/DAPAR documentation built on May 6, 2022, 5:30 p.m.