prepDRdat: prepare dose-reponse data
In nickytong/drexplorer: Dose-response Explorer

Description Usage Arguments Details Value

this function scaled the response by mean reponse in control when necessary

1	prepDRdat(drMat, alpha = 0.01, fitCtr = FALSE, standardize = TRUE)

`drMat`	dose-response matrix as for drFit. the first column being dosage and second column being response. controls are included by specifying dose=0
`alpha`	a scalar for significance level. This specifies the significance level to identify outliers which will be excluded from model fitting. To include all data, set alpha=1.
`fitCtr`	A logic vector specifying whether to include the control points into the model fitting.
`standardize`	whether to standardize (scale) the data based on control points. This should be disabled when no control data is supplied

the standardization means response (e.g. count) is to be scaled by mean control response so that the standardized response is relative viability, usually between 0 and 1. this function first detects outlier data points (using supplied data, either scaled or not scaled). It then scale the data and split the data into two data frames: one for dose not 0 and one for dose at 0 Ideally, outlier detection is better at original count (or signal intensity) due to asymptotic assumption But for data already scaled, detection outlier at this level is what we can do

a list

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