sim1sbind: Simulate one-site ligand receptor binding

Description Usage Arguments Value Examples

View source: R/sim1sbind.R

Description

A sandbox to simulate and visualize random normal heteroscedastic response data. Variances enlarge with the value of y predicted by the model using a constant coefficeint of variation (cv). The data generating formula is derived from the one-site total binding model: y=Bmax*x/(x+kd). Failure errors in the plot fitting subfunction will occasionally happen due to the random data. These are more frequent with higher cv values. Just re-simulate with modified parameter values.

Usage

1
sim1sbind(x, bmax, kd, cv, reps, log = F)

Arguments

x

a vector representing dose or concentration of ligand (exponential or linear values)

bmax

the measured value where the receptor population is completely saturated by ligand (i.e. maximum binding)

kd

the value of x that yields y/Bmax = 0.5 (the equilibrium binding constant)

cv

the coefficient of variation for y replicates

reps

an integer value for number of replicates

log

logical value. Default is FALSE. If TRUE, linear x values are transformed using a log10 function for plotting. Only for visual aesthetic.

Value

ggplot, data

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
dose <- c(1, 3, 10, 30, 100, 300) # eg, in nM units
logdose <- c(1e-3, 3e-3, 1e-2, 3e-2, 1e-1, 3e-1, 1e0, 3e0) # eg, in nM units

set.seed(2345)

binddat <- sim1sbind(dose, bmax = 1000, kd = 50, cv = 0.10, reps = 5, log = FALSE ); binddat

binddat$data #extract the data frame containing x and cv-modified y values

sim1sbind(logdose, bmax = 10000, kd = 5e-2, cv = 0.20, reps = 5, log = TRUE)

TJMurphy/nlfitr documentation built on March 18, 2021, 12:33 p.m.