{ "_id": "6a140987acfb0bcc41d3a0ea", "Package": "Rcurvep", "Type": "Package", "Title": "Concentration-Response Data Analysis using Curvep", "Version": "1.3.2", "Authors@R": "c(\nperson(\"Jui-Hua\", \"Hsieh\", email = \"juihua.hsieh@gmail.com\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-1620-1571\")),\nperson(\"Alexander\", \"Sedykh\", role = c(\"aut\")),\nperson(\"Fred\", \"Parham\", role = c(\"ctb\")),\nperson(\"Yuhong\", \"Wang\", role = c(\"ctb\")),\nperson(\"Tongan\", \"Zhao\", role = c(\"aut\")),\nperson(\"Ruili\", \"Huang\", role = c(\"ctb\"))\n)", "Description": "An R interface for processing concentration-response\ndatasets using Curvep, a response noise filtering algorithm.\nThe algorithm was described in the publications (Sedykh A et\nal. (2011) and Sedykh A (2016)\n). Other parametric fitting\napproaches (e.g., Hill equation) are also adopted for ease of\ncomparison. 3-parameter Hill equation from 'tcpl' package\n(Filer D et al., ) and\n4-parameter Hill equation from Curve Class2 approach (Wang Y et\nal., ) are available. Also,\nmethods for calculating the confidence interval around the\nactivity metrics are also provided. The methods are based on\nthe bootstrap approach to simulate the datasets (Hsieh J-H et\nal. ). The simulated datasets can be\nused to derive the baseline noise threshold in an assay\nendpoint. This threshold is critical in the toxicological\nstudies to derive the point-of-departure (POD).", "Language": "en-US", "BugReports": "https://github.com/moggces/Rcurvep/issues", "License": "MIT + file LICENSE", "URL": "https://github.com/moggces/Rcurvep,\nhttps://moggces.github.io/Rcurvep/", "Encoding": "UTF-8", "LazyData": "true", "RdMacros": "Rdpack", "VignetteBuilder": "knitr", "SystemRequirements": "Java", "RoxygenNote": "7.2.3", "Roxygen": "list(markdown = TRUE)", "Config/pak/sysreqs": "make default-jdk libicu-dev", "Repository": "https://moggces.r-universe.dev", "Date/Publication": "2025-05-30 13:28:32 UTC", "RemoteUrl": "https://github.com/moggces/rcurvep", "RemoteRef": "HEAD", "RemoteSha": "7dd6963393731112109b6a8980539ccb6d0f5db7", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-25 08:29:57 UTC", "User": "root" }, "Author": "Jui-Hua Hsieh [aut, cre] (ORCID:\n),\nAlexander Sedykh [aut],\nFred Parham [ctb],\nYuhong Wang [ctb],\nTongan Zhao [aut],\nRuili Huang [ctb]", 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96, "table": true, "tojson": true }, { "name": "zfishdev_act", "title": "Activity output based on simulated datasets using zfishdev_all dataset", "object": "zfishdev_act", "class": [ "rcurvep", "list" ], "fields": [], "table": false, "tojson": false }, { "name": "zfishdev_all", "title": "Full sets of concentration response datasets from zebrafish developmental toxicity assays", "object": "zfishdev_all", "class": [ "tbl_df", "tbl", "data.frame" ], "fields": [ "endpoint", "chemical", "conc", "n_in", "N" ], "rows": 512, "table": true, "tojson": true } ], "_help": [ { "page": "cal_knee_point", "title": "Calculate the knee point on the exponential-like curve", "topics": [ "cal_knee_point" ] }, { "page": "combi_run_rcurvep", "title": "Run Curvep on datasets of concentration-response data with a combination of Curvep parameters", "topics": [ "combi_run_rcurvep" ] }, { "page": "create_dataset", "title": "Create concentration-response datasets that can be applied in the 'run_rcurvep()'", 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