calculateRatePvals: Calculate a single p-value for each rate

Description Usage Arguments Details Value See Also Examples

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

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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

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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)

INSPEcT documentation built on April 29, 2020, 5:19 a.m.