2nd Rubin's rule Within-Variance Component (all peptides)

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

rubin2wt.all(
  data,
  funcvar = mi4p::within_variance_comp_emmeans,
  metacond,
  is.parallel = FALSE,
  verbose = TRUE
)

Arguments

data

dataset

funcvar

function that should be used to compute the variance

metacond

a factor to specify the groups

is.parallel

should parallel computing be used?

verbose

should messages be displayed?

Value

List of variance-covariance matrices.

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. doi:10.1371/journal.pcbi.1010420 .

Author

Frédéric Bertrand

Examples

library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], 
conditions = attr(datasim,"metadata")$Condition, method = "MLE")
rubin2wt.all(datasim_imp[1:5,,],funcvar = within_variance_comp_emmeans,
attr(datasim,"metadata")$Condition)
#> [[1]]
#>           A         B
#> A 0.1911347 0.0000000
#> B 0.0000000 0.1911347
#> 
#> [[2]]
#>           A         B
#> A 0.1265196 0.0000000
#> B 0.0000000 0.1265196
#> 
#> [[3]]
#>           A         B
#> A 0.2441502 0.0000000
#> B 0.0000000 0.2441502
#> 
#> [[4]]
#>           A         B
#> A 0.1465614 0.0000000
#> B 0.0000000 0.1465614
#> 
#> [[5]]
#>           A         B
#> A 0.1341801 0.0000000
#> B 0.0000000 0.1341801
#>