rubin1.all | R Documentation |
Computes the first Rubin's rule for all the peptides.
rubin1.all(
data,
metacond,
funcmean = meanImp_emmeans,
is.parallel = FALSE,
verbose = FALSE
)
data |
dataset |
metacond |
a factor to specify the groups |
funcmean |
function that should be used to compute the mean |
is.parallel |
Logical, whether or not use parallel computing
(with |
verbose |
Logical, should messages be displayed? |
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. \Sexpr[results=rd]{tools:::Rd_expr_doi("doi:10.1371/journal.pcbi.1010420")}.
library(mi4p)
data(datasim)
datasim_imp <- multi.impute(data = datasim[,-1], conditions =
attr(datasim,"metadata")$Condition, method = "MLE")
rubin1.all(datasim_imp[1:5,,],funcmean = meanImp_emmeans,
attr(datasim,"metadata")$Condition)
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