-
Notifications
You must be signed in to change notification settings - Fork 1
/
README.Rmd
76 lines (56 loc) · 3.69 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# BeeGUTS
<!-- badges: start -->
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
[](https://CRAN.R-project.org/package=BeeGUTS)
[](https://github.com/bgoussen/BeeGUTS/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
The goal of BeeGUTS is to analyse the survival toxicity tests performed for
bee species. It can be used to fit a Toxicokinetic-Toxicodynamic (TKTD) model
adapted for bee standard studies (acute oral, acute contact, and chronic oral studies).
The TKTD model used is the General Unified Threshold model of Survival (GUTS).
The model is based on the following publications:
* Baas, J., Goussen, B., Taenzler, V., Roeben, V., Miles, M., Preuss, T.G., van den Berg, S. and Roessink, I. (2024), Comparing Sensitivity of Different Bee Species to Pesticides: A TKTD modeling approach. Environ Toxicol Chem, 43: 1431-1441. https://doi.org/10.1002/etc.5871
* Baas, J., Goussen, B., Miles, M., Preuss, T.G. and Roessink, I. (2022), BeeGUTS—A Toxicokinetic–Toxicodynamic Model for the Interpretation and Integration of Acute and Chronic Honey Bee Tests. Environ Toxicol Chem, 41: 2193-2201. https://doi.org/10.1002/etc.5423
* Jager T, Albert C, Preuss TG, Ashauer R. General unified threshold model of survival--a toxicokinetic-toxicodynamic framework for ecotoxicology. Environ Sci Technol. 2011 Apr 1;45(7):2529-40. doi: 10.1021/es103092a. Epub 2011 Mar 2. PMID: 21366215.
## Installation
You can install the released version of BeeGUTS from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("BeeGUTS")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("bgoussen/BeeGUTS")
```
## Documentation
Detailed documentation is available [here](https://github.com/bgoussen/BeeGUTS/blob/dev-docs/docs/home.md)
## Example
This is a basic example which shows you how to solve a common problem:
```{r example}
library(BeeGUTS)
file_location <- system.file("extdata", "betacyfluthrin_chronic_ug.txt", package = "BeeGUTS") # Load the path to one of the example file
lsData <- dataGUTS(file_location = file_location, test_type = 'Chronic_Oral', cstConcCal = FALSE) # Read the example file
plot(lsData) # Plot the data
fit <- fitBeeGUTS(lsData, modelType = "SD", nIter = 3000, nChains = 1) # Fit a SD model. This can take some time...
traceplot(fit) # Produce a diagnostic plot of the fit
plot(fit) # Plot the fit results
summary(fit) # Gives a summary of the results
validation <- validate(fit, lsData, fithb = TRUE) # produce a validation of the fit after refitting background mortality from the control data (here it uses the same dataset as calibration as an example, so not relevant…)
plot(validation) # plot the validation results
dataPredict <- data.frame(time = c(1:5, 1:15), conc = c(rep(5, 5), rep(15, 15)), replicate = c(rep("rep1", 5), rep("rep3", 15))) # Prepare data for forwards prediction
prediction <- predict(fit, dataPredict) # Perform forwards prediction. At the moment, no concentration recalculation is performed in the forwards prediction. The concentrations are taken as in a chronic test
plot(prediction) # Plot of the prediction results
```