In lshen1/drexplorer2: Dose-response Explorer2

knitr::opts_chunk$set(
  message = FALSE,
  digits = 3,
  collapse = TRUE,
  comment = "#>"
  )
options(digits = 3)

We provide a wrapper function, fitOneExp(), incorporating outlier detection, fitting multiple models, selecting the best model and estimating IC values.

Users can specify multiple models from the drc and DoseFinding packages using the models parameter. An example is shown below.

library(drexplorer2)
data(ryegrass)

fitExp <- fitOneExp(ryegrass[, c(2, 1)],
                    drug = '', cellLine = '', unit = '',
                    models=c('sigEmax', 'LL.4', 'LL.5', 'LL.3', 'LL.3u', 'logistic'),
                    alpha = 0.05, interpolation = TRUE)

The fitted models can be compared through the plotOneExp function as below:

plotOneExp(fitExp, main = 'Dose-Response Curves from Multiple Models')

The best model based on Residual Standard Error (RSE) can be obtained as shown below.

## This is the bast model:
bM <- fitExp$bestModel
bM

## RSE from all models fitted:
fitExp$RSEs

## IC50 from all models fitted:
fitExp$IC50

## best model fitted:
fitExp$fit[[bM]]@fit