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. doi:10.1371/journal.pcbi.1010420
.
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)
#> A B
#> A 0.1911347 0.0000000
#> B 0.0000000 0.1911347