pod_envelope_analysis: This function calculates the chemical's point of departure.
In aop: Adverse Outcome Pathway Analysis

Description Usage Arguments Value Examples

This function calculates the chemical's point of departure based on the concentration-response data.

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pod_envelope_analysis(bmr_obj, slope_data, slope_threshold = 1,
  lower_interpolation_range, upper_interpolation_range, interval_size,
  agonist_assay = TRUE)

`bmr_obj`	a `bmr` object that holds all of the bootstrap metaregression models produced.
`slope_data`	the `data.frame` object that contains the concentration and slope data.
`slope_threshold`	the `numeric` object that sets the threshold for the slope. This determines the upper bound on the concentration range that is determined to be the asymptote. In other words, the asymptote is defined as that region that has a slope less than the threshold at the lower end of the concentration-response curve.
`lower_interpolation_range`	a `numeric` value where the interpolation should be bounded on the lower end.
`upper_interpolation_range`	a `numeric` value where the interpolation should be bounded on the upper end.
`interval_size`	a `numeric` value that specifies how large the interval should be between each value used for interpolation between the lower and upper bounds.
`agonist_assay`	a `boolean` value that specifies if the assay is an agonist or antagonist assay.

a two column data.frame that contains the chemical's point of departure and the threshold value.

bmr_obj <- bootstrap_metaregression(oxybenzone, 15, 100)
slope_pod <- slope_pod_analysis(bmr_obj, 0.0001, 10, 0.1)
pod_and_threshold <- pod_envelope_analysis(bmr_obj, slope_pod,
  slope_threshold = 10, min(oxybenzone$Concentration),
  max(oxybenzone$Concentration), interval_size = 0.1)