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It uses response surface approach to study deviations of the observed effects from a predicted response surface.\n\nTo install the package from CRAN, run:\n\n```r\ninstall.packages(\"BIGL\")\n```\n\nTo install the latest development version from Github, we suggest using `devtools`:\n\n```r\ndevtools::install_github(\"OpenAnalytics/BIGL\", build_vignettes = TRUE)\n```\n\n`BIGL` methodology currently allows generalized Loewe, classical Loewe and Highest Single Agent models for predicted response surface generation. Generalized Loewe approach allows in particular to treat compounds with differing maximal response and is detailed in the accompanying BIGL paper (pending submission).\n\nScientific workflow is briefly explained in the `methodology` vignette provided with the package. `analysis` vignette will guide the user through the main functionality of the package. If you have built the vignettes for the package during the installation, these can be accessed by\n\n```r\n## User guide\nvignette(\"analysis\", package = \"BIGL\")\n\n## Methodology overview\nvignette(\"methodology\", package = \"BIGL\")\n```\n\nIf you have `shiny` and `DT` packages installed, you might be interested in trying out the demo for the type of response surfaces that the package works with.\n\n```r\nlibrary(BIGL)\nrunBIGL()\n```\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenanalytics%2Fbigl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopenanalytics%2Fbigl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenanalytics%2Fbigl/lists"}