Fits dose-response curves to data given by the user and returns the ABC of the fitted curves.
Source:R/computeABC.R
computeABC.Rd
Fits dose-response curves to data given by the user and returns the ABC of the fitted curves.
Usage
computeABC(
conc1,
conc2,
viability1,
viability2,
Hill_fit1,
Hill_fit2,
conc_as_log = FALSE,
viability_as_pct = TRUE,
trunc = TRUE,
verbose = TRUE
)
Arguments
- conc1
numeric
is a vector of drug concentrations.- conc2
numeric
is a vector of drug concentrations.- viability1
numeric
is a vector whose entries are the viability values observed in the presence of the drug concentrations whose logarithms are in the corresponding entries of conc1, expressed as percentages of viability in the absence of any drug.- viability2
numeric
is a vector whose entries are the viability values observed in the presence of the drug concentrations whose logarithms are in the corresponding entries of conc2, expressed as percentages of viability in the absence of any drug.- Hill_fit1
list
orvector
In the order: c("Hill Slope", "E_inf", "EC50"), the parameters of a Hill Slope as returned by logLogisticRegression. If conc_as_log is set then the function assumes logEC50 is passed in, and if viability_as_pct flag is set, it assumes E_inf is passed in as a percent. Otherwise, E_inf is assumed to be a decimal, and EC50 as a concentration.- Hill_fit2
lis
orvector
In the order: c("Hill Slope", "E_inf", "EC50"), the parameters of a Hill Slope as returned by logLogisticRegression. If conc_as_log is set then the function assumes logEC50 is passed in, and if viability_as_pct flag is set, it assumes E_inf is passed in as a percent. Otherwise, E_inf is assumed to be a decimal, and EC50 as a concentration.- conc_as_log
logical
, if true, assumes that log10-concentration data has been given rather than concentration data.- viability_as_pct
logical
, if false, assumes that viability is given as a decimal rather than a percentage, and returns ABC as a decimal. Otherwise, viability is interpreted as percent, and AUC is returned 0-100.- trunc
logical
, if true, causes viability data to be truncated to lie between 0 and 1 before curve-fitting is performed.- verbose
logical
, if true, causes warnings thrown by the function to be printed.
Examples
dose1 <- c(0.0025,0.008,0.025,0.08,0.25,0.8,2.53,8)
viability1 <- c(108.67,111,102.16,100.27,90,87,74,57)
dose2 <- c(0.0025,0.008,0.025,0.08,0.25,0.8,2.53,8)
viability2 <- c(100.94,112.5,86,104.16,75,68,48,29)
computeABC(dose1, dose2, viability1, viability2)
#> Warning: Warning: y data exceeds negative control.
#> Warning: Warning: y data exceeds negative control.
#> [1] 8.844687