Package: Rcurvep 1.3.1
Rcurvep: Concentration-Response Data Analysis using Curvep
An R interface for processing concentration-response datasets using Curvep, a response noise filtering algorithm. The algorithm was described in the publications (Sedykh A et al. (2011) <doi:10.1289/ehp.1002476> and Sedykh A (2016) <doi:10.1007/978-1-4939-6346-1_14>). Other parametric fitting approaches (e.g., Hill equation) are also adopted for ease of comparison. 3-parameter Hill equation from 'tcpl' package (Filer D et al., <doi:10.1093/bioinformatics/btw680>) and 4-parameter Hill equation from Curve Class2 approach (Wang Y et al., <doi:10.2174/1875397301004010057>) are available. Also, methods for calculating the confidence interval around the activity metrics are also provided. The methods are based on the bootstrap approach to simulate the datasets (Hsieh J-H et al. <doi:10.1093/toxsci/kfy258>). The simulated datasets can be used to derive the baseline noise threshold in an assay endpoint. This threshold is critical in the toxicological studies to derive the point-of-departure (POD).
Authors:
Rcurvep_1.3.1.tar.gz
Rcurvep_1.3.1.tar.gz(r-4.5-noble)Rcurvep_1.3.1.tar.gz(r-4.4-noble)
Rcurvep_1.3.1.tgz(r-4.4-emscripten)Rcurvep_1.3.1.tgz(r-4.3-emscripten)
Rcurvep.pdf |Rcurvep.html✨
Rcurvep/json (API)
NEWS
# Install 'Rcurvep' in R: |
install.packages('Rcurvep', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/moggces/rcurvep/issues
- zfishbeh - Subsets of concentration response datasets from zebrafish neurotoxicity assays
- zfishdev - Subsets of concentration response datasets from zebrafish developmental toxicity assays
- zfishdev_act - Activity output based on simulated datasets using zfishdev_all dataset
- zfishdev_all - Full sets of concentration response datasets from zebrafish developmental toxicity assays
Last updated 11 months agofrom:a0a26c319a. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 05 2024 |
R-4.5-linux | OK | Dec 05 2024 |
Exports:cal_knee_pointcombi_run_rcurvepcreate_datasetcurvepcurvep_defaultsestimate_dataset_bmrfit_cc2_modlfit_modlsget_hill_fit_configmerge_rcurvep_objsrun_fitrun_rcurvepsummarize_fit_outputsummarize_rcurvep_output
Dependencies:bootclicodetoolscolorspacecpp11digestdplyrfansifarverfurrrfuturegenericsggplot2globalsgluegtableisobandlabelinglatticelifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmeparallellypillarpkgconfigpurrrR6rbibutilsRColorBrewerRdpackrJavarlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Parallel Computing Examples Using Rcurvep
Rendered fromfuture_rcurvep.Rmd
usingknitr::rmarkdown
on Dec 05 2024.Last update: 2024-01-10
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Practical applications using Rcurvep package
Rendered frompractical_rcurvep.Rmd
usingknitr::rmarkdown
on Dec 05 2024.Last update: 2024-01-10
Started: 2021-01-07