Description Usage Arguments Value Author(s) See Also Examples

View source: R/multtest.TcGSA.R

This function computes the p-value of the likelihood ratios and apply a multiple testing correction.

1 2 3 4 5 6 7 | ```
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`

1 2 3 4 5 6 7 8 9 10 11 | ```
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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