sim_cell_lines: Simulate Cell Lines
In chapmandu2/pgxsim: Simulate Dose Response Curves For Pharmacogenomics Analysis

Description Usage Arguments Value Examples

Simulate cell lines with predefined genetic and drug response characteristics.

1 2	sim_cell_lines(n, type = "d", prop = 0.2, prho = 0.9, mu = 0, sd = 0.1, beta = 1, lb = -4, ub = Inf, sd_prop = 0, sd_add = 0)

`n`	Number of cell lines to simulate
`type`	Whether genetic covariate is a discrete (d) or continuous (c) variable
`prop`	Proportion of cell lines with a discrete characteristic
`prho`	value of correlation coefficient (0-1 for continuous, ignored for discrete)
`mu`	mean of the truncated normal distribution
`sd`	standard deviation of the truncated normal distribution
`beta`	value of the genetic coefficient to recover - note that this is on a log scale
`lb`	lower bound of the pIC50 distribution
`ub`	upper bound of the pIC50 distribution
`sd_prop`	Cell line specific proportional dose response variance
`sd_add`	Cell line specific additive dose response variance

A tibble containing cell line data

library(dplyr)
set.seed(10000)
sim_cell_lines(n=10, type='d', prop=0.2, mu=1, sd=0.1, beta=1)
sim_cell_lines(n=10, type='c', mu=1, sd=0.1, beta=1, prho=0.6)