tests/examplewithanchoringdata.R

In DRomics: Dose Response for Omics

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 = TRUE)
  plot(f, plot.type = "dose_residuals")
  
}

# various plot of fitted curves (without data)
if (visualize)
{
  curvesplot(f$fitres, xmax = max(f$omicdata$dose), 
             facetby = "model", colorby = "model")
  curvesplot(f$fitres, xmax = max(f$omicdata$dose), 
             facetby = "typology")
  
  # plot of selection of curves
  curvesplot(f$fitres[f$fitres$trend == "U", ], xmax = max(f$omicdata$dose), 
             facetby = "id")
  
}


# 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))
}

# 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)
  
}