library(DRomics)
visualize <- FALSE ## put to TRUE for a manual check of plots
doboot <- FALSE
# importation and check of apical anchoring data
# datafilename <- system.file("extdata", "apical_anchoring.txt", package="DRomics")
# (o <- continuousanchoringdata(datafilename, backgrounddose = 0.1, check = TRUE))
data("Scenedesmus_apical")
(o <- continuousanchoringdata(Scenedesmus_apical, backgrounddose = 0.1, check = TRUE))
# Use of only one endpoint
#(o <- continuousanchoringdata(Scenedesmus_apical[c(1,2), ],
# backgrounddose = 0.1,check = TRUE)) # growth
# (o <- continuousanchoringdata(Scenedesmus_apical[c(1,3), ],
# backgrounddose = 0.1, check = TRUE)) # photosynthesis
if (visualize)
plot(o)
# item selection using the three methods
(s_quad <- itemselect(o, select.method = "quadratic", FDR = 0.05))
if (visualize)
{
(s_lin <- itemselect(o, select.method = "linear", FDR = 0.05))
(s_ANOVA <- itemselect(o, select.method = "ANOVA", FDR = 0.05))
}
# fit
(f <- drcfit(s_quad, progressbar = TRUE))
if (visualize)
{
f$fitres
plot(f)
plot(f, dose_log_transfo = FALSE)
plot(f, plot.type = "dose_residuals")
}
# calculation of benchmark doses
# options in shiny : z (numerical positive value), x (numerical positive value : percentage)
(r <- bmdcalc(f, z = 1, x = 10))
if (visualize)
{
r$res
# plot of BMD with gradient
bmdplotwithgradient(r$res, xmax = max(f$omicdata$dose))
}
# various plot of fitted curves (without data)
if (visualize)
{
curvesplot(r$res, xmax = max(f$omicdata$dose),
facetby = "model", colorby = "model")
curvesplot(r$res, xmax = max(f$omicdata$dose),
facetby = "typology")
}
# Calculation of confidence intervals on BMDs by Bootstrap
if (doboot)
{
niter <- 1000
niter <- 10
(b <- bmdboot(r, niter = niter)) # niter should be fixed at least at 1000 to get a reasonable precision
if (visualize)
plot(b)
}
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