Retrieve a single p-value for each rate

This method is used to retrieve all the p-values combined with Brown's method that combines the results of the
log likelihood ratio test results for all pairs tested for each rate and all genes. P-values will change
according to the threshold set for the chi-squared test because it influences the model that will be taken into
consideration to perform log likelihood ratio tests. To have a sense of the best parameter to choose, a sythetic
data-set can be built and tested (`makeSimModel`

, `makeSimDataset`

)
In case 'aic' has been selected via `modelSelection`

method,
this method assigns the chi-squared test result of the model selected by AIC
to the respective variable rates

1 2 3 4 5 6 7 |

`object` |
An object of class INSPEcT or INSPEcT_model |

`cTsh` |
A numeric representing the threshold for the chi-squared test to consider a model as valid |

ratePvlas retrieve a single p-value for each rate thanks to multiple log likelihood tests performed on nested models that has a chi-squared test below the selected threshold. Among the many p-values that log likelihood ratio test calculate, a single p-value is obtaied applying Brown's method for combining dependent p-values.

A matrix containing p-values calculated for each rate

1 2 3 4 5 6 7 | ```
data('mycerIds10', package='INSPEcT')
ratePvals(mycerIds10)
# calculate agin the p-values with Brown with a different threshold
# for considering a model valid for the log likelihood ratio test
ratePvals(mycerIds10, cTsh=.2)
# Set permaenently the chi-squared threshold at .2 for mycerIds10 object
thresholds(mycerIds10)$chisquare <- .2
``` |

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