Create a PDF and HTML report with results from a growth curve analysis workflow
Source:R/report_functions.R
growth.report.Rdgrowth.report requires a grofit object and creates a report in PDF and HTML format that summarizes all results.
Arguments
- grofit
A
grofitobject created withgrowth.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
NULLDefine the name of the report files. IfNULL, 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
TRUEor notFALSE?- 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.
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)
}