fitOneExp: Fit multiple dose response models for a single drug in a...

In nickytong/drexplorer: Dose-response Explorer

Description

the dose response mode is usually fitted with original dose (not log10 transformed). The computed ICx values however, can be in either log10 scale or the original scale.

Usage

fitOneExp(dat, drug = NA, cellLine = NA, unit = NA, models = c("LL.3",
  "LL.3u", "sigEmax", "logistic", "linlog"), cols = NA, log.d = TRUE,
  percentile = seq(0.1, 0.9, by = 0.1), alpha = 0.01, fitCtr = FALSE,
  standardize = TRUE, interpolation = TRUE, plot = FALSE,
  transparency = 1, ...)

Arguments

dat	a 2-column data frame with first column as dose and second column response. Controls are decided by dose=0
drug	drug for this analysis
cellLine	cell line for this analysis
unit	unit of drug concentration
models	models the user may specify
cols	colors of dose-response curves
log.d	in computed ICx values, whether to return the log10 dose or the dose without this transformation
percentile	IC percentile
alpha	outlier significance level
fitCtr	whether the model is fitted with control data
standardize	whether to standardize (scale) the data based on control points. This should be disabled when no control data is supplied
interpolation	whether calculate ICx through interpolation or through root finding. This parameter is passed to computeIC() function. When interpolation=TRUE, ICx value will be bounded by observed minimum and maximum dose; otherwise, ICx is calculated through root finding and thus can be outside this boundary (extrapolated).
plot	whether to draw the dose response curve
transparency	a value between 0 and 1 specifying transparency through alpha blending; transparency=0 means totally transparent.
...	additional parameters to plotOneExp()

Value

a list containing elements with:

fits,

models,

cols,

ICmat, IC matrix from all specified models as well as RSE and model name

ICx, IC values from the best model

datWithOutlierStatus the input data with outlier status appended

bestModel the best model by RSE

RSEs

nickytong/drexplorer documentation built on May 23, 2019, 5:08 p.m.