Run Curvep on datasets of concentration-response data with a combination of Curvep parameters

It simplifies the steps of run_rcurvep() by wrapping the create_dataset() in the function.

combi_run_rcurvep(
  d,
  n_samples = NULL,
  vdata = NULL,
  mask = 0,
  keep_sets = c("act_set", "resp_set", "fp_set"),
  ...
)

Arguments

d	Datasets with concentration-response data. Examples are zfishbeh and zfishdev.
n_samples	NULL (default) for not to simulate responses or an integer number to indicate the number of responses per concentration to simulate.
vdata	NULL (default) for not to simulate responses or a vector of numeric responses in vehicle control wells to use as error. This parameter only works when n_samples is not NULL; an experimental feature.
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.
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

run_rcurvep()

Examples

data(zfishbeh)

# 2 simulated sample curves +
# using two thresholds +
# mask the response at the higest concentration
# only to output the act_set

out <- combi_run_rcurvep(
  zfishbeh,
  n_samples = 2,
  TRSH = c(5, 10),
  mask = 1,
  keep_sets = "act_set")

# create the zfishdev_act dataset
# \donttest{

 data(zfishdev_all)
 zfishdev_act <- combi_run_rcurvep(
   zfishdev_all, n_samples = 100, keep_sets = c("act_set"),TRSH = seq(5, 95, by = 5),
   RNGE = 1000000, CARR = 20, seed = 300
 )
# }