This function computes the p-value of the likelihood ratios and apply a multiple testing correction.
a TcGSA object.
the threshold at which the FDR or the FWER should be controlled.
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: "
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).
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
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
raw_pval, the 5th column is the adjusted p-value of the
mixed likelihood ratio test
Boris P. Hejblum
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## Not run: 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 ## End(Not run)
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