R/rubin2bt_all.R
rubin2bt.all.Rd
Computes the between-imputation component in the 2nd Rubin's rule for all peptides.
rubin2bt.all( data, funcmean = meanImp_emmeans, metacond, is.parallel = FALSE, verbose = FALSE )
data | dataset |
---|---|
funcmean | function that should be used to compute the mean |
metacond | a factor to specify the groups |
is.parallel | should parallel computing be used? |
verbose | should messages be displayed? |
List of variance-covariance matrices.
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. arxiv:2108.07086. https://arxiv.org/abs/2108.07086.
Frédéric Bertrand
library(mi4p) data(datasim) datasim_imp <- multi.impute(data = datasim[,-1], conditions = attr(datasim,"metadata")$Condition, method = "MLE") rubin2bt.all(datasim_imp[1:5,,],funcmean = meanImp_emmeans, attr(datasim,"metadata")$Condition)#> [[1]] #> [,1] [,2] #> [1,] 0 0 #> [2,] 0 0 #> #> [[2]] #> [,1] [,2] #> [1,] 0 0 #> [2,] 0 0 #> #> [[3]] #> [,1] [,2] #> [1,] 0 0 #> [2,] 0 0 #> #> [[4]] #> [,1] [,2] #> [1,] 0 0 #> [2,] 0 0 #> #> [[5]] #> [,1] [,2] #> [1,] 0 0 #> [2,] 0 0 #>