Description Usage Arguments Details Value See Also Examples

This method is used to calculate all the p-values relative to the variability of synthesis, processing and degradation rates. For object modeled with nascent RNA or when non-functional modeling was used, the variability is calculated using the confidence intervals. For objects modeled without nascent RNA, model selection is performed by comparing the likelihood of different (nested) models.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
calculateRatePvals(
object,
modelSelection = c("aic", "llr", "hib"),
preferPValue = TRUE,
padj = TRUE,
p_goodness_of_fit = 0.1,
p_variability = rep(0.05, 3),
limitModelComplexity = FALSE
)
## S4 method for signature 'INSPEcT'
calculateRatePvals(
object,
modelSelection = c("aic", "llr", "hib"),
preferPValue = TRUE,
padj = TRUE,
p_goodness_of_fit = 0.1,
p_variability = rep(0.05, 3),
limitModelComplexity = FALSE
)
``` |

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

`modelSelection` |
'aic' compares nested models closest to the one with lowest AIC, 'llr' compares all nested models, 'hib' is a mix between the previous two. (default 'aic') |

`preferPValue` |
a logical, if TRUE (default) limit the search for best models among the ones with succeded the goodness of fit test. |

`padj` |
a logical, if TRUE (default) correct the p-values for multiple testing |

`p_goodness_of_fit` |
a numeric, the threshold for the goodness-of-fit test (default = .1) |

`p_variability` |
a numeric, a vector with the thresholds for the p-value of the variability test (one threshold for each rate, default = rep(.05, 3)) |

`limitModelComplexity` |
a logical that limits the complexity of the function used to describe dynamics to the length of the time-course (default = FALSE) |

ratePvals retrieve a single p-value for each rate and gene associated to its variability (null hypothesis = the rate is not changing between the conditions)

A matrix containing p-values calculated for each rate

1 2 3 | ```
nascentInspObj10 <- readRDS(system.file(package='INSPEcT', 'nascentInspObj10.rds'))
# Set the chi-squared threshold at .2 for nascentInspObj10 object
nascentInspObj10 <- calculateRatePvals(nascentInspObj10, p_goodness_of_fit=.2)
``` |

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