View source: R/multtest.TcGSA.R
| multtest.TcGSA | R Documentation |
This function computes the p-value of the likelihood ratios and apply a multiple testing correction.
multtest.TcGSA(
tcgsa,
threshold = 0.05,
myproc = "BY",
exact = TRUE,
nbsimu_pval = 1e+06
)
tcgsa |
a TcGSA object. |
threshold |
the threshold at which the FDR or the FWER should be controlled. |
myproc |
a vector of character strings containing the names of the
multiple testing procedures for which adjusted p-values are to be computed.
This vector should include any of the following: " |
exact |
logical flag indicating whether the raw p-values should be computed from the
exact asymptotic mixture of chi-square, or simulated (longer and not better).
Default is |
nbsimu_pval |
the number of observations under the null distribution to
be generated in order to compute the p-values. Default is |
multtest.TcGSA returns an dataframe with 5 variables. The
rows correspond to the gene sets under scrutiny. The 1st column is the
likelihood ratios LR, the 2nd column is the convergence status of the
model under the null hypothesis CVG_H0, the 3rd column is the
convergence status of the model under the alternative hypothesis
CVG_H1, the 4th column is the raw p-value of the mixed likelihood
ratio test raw_pval, the 5th column is the adjusted p-value of the
mixed likelihood ratio test adj_pval.
Boris P. Hejblum
TcGSA.LR,
mt.rawp2adjp,
signifLRT.TcGSA
if(interactive()){
data(data_simu_TcGSA)
tcgsa_sim_1grp <- TcGSA.LR(expr=expr_1grp, gmt=gmt_sim, design=design,
subject_name="Patient_ID", time_name="TimePoint",
time_func="linear", crossedRandom=FALSE)
mtt <- multtest.TcGSA(tcgsa_sim_1grp, threshold = 0.05,
myproc = "BY", nbsimu_pval = 1000)
mtt
}
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