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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