rubin2.all {mi4p} | R Documentation |
Computes the 2nd Rubin's rule (all peptides)
Description
Computes the total variance-covariance component in the 2nd Rubin's rule for all peptides.
Usage
rubin2.all(
data,
metacond,
funcmean = meanImp_emmeans,
funcvar = within_variance_comp_emmeans,
is.parallel = FALSE,
verbose = FALSE
)
Arguments
data |
dataset |
metacond |
a factor to specify the groups |
funcmean |
function that should be used to compute the mean |
funcvar |
function that should be used to compute the variance |
is.parallel |
should parallel computing be used? |
verbose |
should messages be displayed? |
Value
List of variance-covariance matrices.
Author(s)
Frédéric Bertrand
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.
Examples
library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions =
attr(datasim,"metadata")$Condition, method = "MLE")
rubin2.all(datasim_imp[1:5,,],attr(datasim,"metadata")$Condition)
[Package mi4p version 1.1 Index]