run_rcurvep: Run Curvep on datasets of concentration-response data

Description Usage Arguments Value See Also Examples

View source: R/rcurvep_onerun.R

Description

The concentration-response relationship per endpoint and chemical has to be 1-to-1. If not, use create_dataset() for pre-processing or use combi_run_rcurvep(), which has both pre-processing and more flexible parameter controls.

Usage

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run_rcurvep(
  d,
  mask = 0,
  config = curvep_defaults(),
  keep_sets = c("act_set", "resp_set", "fp_set"),
  ...
)

Arguments

d

Datasets with columns: endpoint, chemical, conc, and resp, mask (optional) Example datasets as zfishbeh. It is required that the baseline of responses in the resp column to be 0.

mask

Default = 0, for no mask (values in the mask column all 0). Use a vector of integers to mask the responses: 1 to mask the response at the highest concentration; 2 to mask the response at the second highest concentration, and so on. If mask column exists, the setting will be ignored.

config

Default configurations set by curvep_defaults().

keep_sets

The types of output to be reported. Allowed values: act_set, resp_set, fp_set. Multiple values are allowed. act_set is the must.

  • act_set: activity data

  • resp_set: response data

  • fp_set: fingerprint data

...

Curvep settings. See curvep_defaults() for allowed parameters. These can be used to overwrite the default values.

Value

An rcurvep object. It has two components: result, config The result component is also a list of output sets depending on the parameter, keep_sets. The config component is a curvep_config object.

Often used columns in the act_set: AUC (area under the curve), wAUC (weighted AUC), POD (point-of-departure), EC50 (Half maximal effective concentration), nCorrected (number of corrected points).

See Also

create_dataset(), combi_run_rcurvep(), curvep_defaults().

Examples

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data(zfishbeh)
d <- create_dataset(zfishbeh)

# default
out <- run_rcurvep(d)

# change TRSH
out <- run_rcurvep(d, TRSH = 30)

# mask response at highest and second highest concentration
out <- run_rcurvep(d, mask = c(1, 2))

Rcurvep documentation built on Jan. 8, 2021, 2:37 a.m.