calculateRatePvals {INSPEcT} | R Documentation

## Calculate a single p-value for each rate

### Description

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.

### Usage

    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
    )

### Arguments

`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)

### Details

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)

### Value

A matrix containing p-values calculated for each rate

### See Also

`makeSimModel`, `makeSimDataset`

### Examples

    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)

[Package INSPEcT version 1.17.15 Index]