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growth.report requires a grofit object and creates a report in PDF and HTML format that summarizes all results.

Usage

growth.report(
  grofit,
  out.dir = tempdir(),
  out.nm = NULL,
  ec50 = FALSE,
  format = c("pdf", "html"),
  export = FALSE,
  parallelize = TRUE,
  ...
)

Arguments

grofit

A grofit object created with growth.workflow.

out.dir

(Character) The path or name of the folder in which the report files are created. If NULL, the folder will be named with a combination of 'Report.growth_' and the current date and time.

out.nm

Character or NULL Define the name of the report files. If NULL, the files will be named with a combination of 'GrowthReport_' and the current date and time.

ec50

(Logical) Display results of dose-response analysis (TRUE) or not (FALSE).

format

(Character) Define the file format for the report, PDF ('pdf') and/or HTML ('html'). Default: (c('pdf', 'html'))

export

(Logical) Shall all plots generated in the report be exported as individual PDF and PNG files TRUE or not FALSE?

parallelize

(Logical) Create plots using all but one available processor cores (TRUE) or only a single core (FALSE).

...

Further arguments passed to create a report. Currently supported:

  • mean.grp: Define groups to combine into common plots in the report based on sample identifiers. Partial matches with sample/group names are accepted. Can be 'all', a string vector, or a list of string vectors. Note: The maximum number of sample groups (with unique condition/concentration indicators) is 50. If you have more than 50 groups, option 'all' will produce the error ! Insufficient values in manual scale. [Number] needed but only 50 provided.

  • mean.conc: Define concentrations to combine into common plots in the report. Can be a numeric vector, or a list of numeric vectors.

Value

NULL

Details

The template .Rmd file used within this function can be found within the QurvE package installation directory.

Examples

if (FALSE) {
# Create random growth data set
  rnd.data <- rdm.data(d = 35, mu = 0.8, A = 5, label = 'Test1')


  # Run growth curve analysis workflow
  res <- growth.workflow(time = rnd.data$time,
                         data = rnd.data$data,
                         fit.opt = 's',
                         ec50 = FALSE,
                         export.res = FALSE,
                         suppress.messages = TRUE,
                         parallelize = FALSE)

  growth.report(res, out.dir = tempdir(), parallelize = FALSE)
}