Computes the within-variance component in the 2nd Rubin's rule for a given peptide.

rubin2wt.one(peptide, data, funcvar, metacond)

Arguments

peptide

peptide for which the variance-covariance matrix should be derived.

data

dataset

funcvar

function that should be used to compute the variance

metacond

a factor to specify the groups

Value

A variance-covariance matrix.

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. arxiv:2108.07086. https://arxiv.org/abs/2108.07086.

Author

Frédéric Bertrand

Examples

library(mi4p) data(datasim) datasim_imp <- multi.impute(data = datasim[,-1], conditions = attr(datasim,"metadata")$Condition, method = "MLE") rubin2wt.one(1,datasim_imp,funcvar=within_variance_comp_emmeans, attr(datasim,"metadata")$Condition)
#> [,1] [,2] #> [1,] 0.1911347 0.0000000 #> [2,] 0.0000000 0.1911347