rubin1.one | R Documentation |
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.
Frédéric Bertrand
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.
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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.