Computes the first Rubin's rule for all the peptides.
rubin1.all(
data,
metacond,
funcmean = meanImp_emmeans,
is.parallel = FALSE,
verbose = FALSE
)
dataset
a factor to specify the groups
function that should be used to compute the mean
Logical, whether or not use parallel computing
(with foreach
).
Logical, should messages be displayed?
A vector of estimated parameters.
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 .
library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions =
attr(datasim,"metadata")$Condition, method = "MLE")
rubin1.all(datasim_imp[1:5,,],funcmean = meanImp_emmeans,
attr(datasim,"metadata")$Condition)
#> [,1] [,2]
#> [1,] 99.02599 200.2387
#> [2,] 100.18124 199.4532
#> [3,] 99.62693 200.1038
#> [4,] 100.09296 200.1658
#> [5,] 100.56314 199.6811