Computes the first Rubin's rule for a given peptide.
rubin1.one(peptide, data, funcmean = meanImp_emmeans, metacond)
peptide | peptide for which the variance-covariance matrix should be derived. |
---|---|
data | dataset |
funcmean | function that should be used to compute the mean |
metacond | a factor to specify the groups |
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. 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")$Condition, method = "MLE") rubin1.one(1,datasim_imp,funcmean = meanImp_emmeans, attr(datasim,"metadata")$Condition)#> [1] 99.02599 200.23868