rubin2.all: Computes the 2nd Rubin's rule (all peptides)
In mi4p: Multiple Imputation for Proteomics

rubin2.all

R Documentation

Computes the 2nd Rubin's rule (all peptides)

Description

Computes the total variance-covariance component in the 2nd Rubin's rule for all peptides.

Usage

rubin2.all(
  data,
  metacond,
  funcmean = meanImp_emmeans,
  funcvar = within_variance_comp_emmeans,
  is.parallel = FALSE,
  verbose = FALSE
)

Arguments

`data`	dataset
`metacond`	a factor to specify the groups
`funcmean`	function that should be used to compute the mean
`funcvar`	function that should be used to compute the variance
`is.parallel`	should parallel computing be used?
`verbose`	should messages be displayed?

Value

List of variance-covariance matrices.

Author(s)

Frédéric Bertrand

References

M. Chion, Ch. Carapito and F. Bertrand (2021). Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics. \Sexpr[results=rd]{tools:::Rd_expr_doi("doi:10.1371/journal.pcbi.1010420")}.

Examples

library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions = 
attr(datasim,"metadata")$Condition, method = "MLE")
rubin2.all(datasim_imp[1:5,,],attr(datasim,"metadata")$Condition)

mi4p documentation built on Oct. 3, 2024, 1:11 a.m.