Detect the Shape of Dose-Response Curves

Provides functions for hormesis screening by classifying the shapes of dose-response curves based on semiparametric tests. The shapes are indications of different potential toxicology effect. It also offers a scalable visualization scheme to present testing conclusions for large-scale dataset with a large number of dose-response curves. For more information, see Jin et al. (2026) < https://github.com/YinglJin-0203/shorm/blob/main/Manuscripts/BotanicalHormesisTestingFinalDraft.docx>.

shorm

Overview

The shorm package provides functions for hormesis screening by classifying the shapes of dose-response curves based on semiparametric tests. The shapes are indications of different potential toxicology effect. It also offers a scalable visualization scheme to present testing conclusions for large-scale dataset with a large number of dose-response curves.

Installation

You can install the development version of shorm from GitHub with:

# install.packages("devtools")
devtools::install_github("YinglJin-0203/shorm")

Usage and Examples

Generate a Data Set

x <- seq(0, 1, length.out = 48)
y <- 2*sqrt(x)+rnorm(48)
y[17:32] <- y[17:32]+0.5
y[33:48] <- y[33:48]+1
curve <- data.frame(x, y)
curve$rep <- rep(1:3, each = 16)

Single SHARP Test

Fixed-model based test

sharpt <- SHARPtest(curve, xName = "x", yName = "y")

Mixed-model based test

sharptm <- SHARPtest(curve, mixed = TRUE, xName = "x", yName = "y", rName = "rep")

Repeated SHARP Test

Fixed-model based test

rsharpt <- RepeatSHARP(curve, nRep = 10, xName = "x", yName = "y")

Mixed-model based test

rsharptm <- RepeatSHARP(curve, nRep = 10, mixed = TRUE, xName = "x", yName = "y", rName = "rep")

Visualize Results

SharpScatter(sharpt[1], sharpt[2], sharpt[3], sharpt[4])