{ "_id": "6a438df68e0887cec9b7137b", "Package": "oncoPredict", "Type": "Package", "Title": "Drug Response Modeling and Biomarker Discovery", "Version": "1.3", "URL": "https://github.com/HuangLabUMN/oncoPredict", "BugReports": "https://github.com/HuangLabUMN/oncoPredict/issues", "Authors@R": "c(\nperson(given = 'Robert',\nfamily = 'Gruener',\nrole = c(\"aut\", \"cre\"),\nemail = 'rgruener@umn.edu',\ncomment = c(ORCID = \"0000-0002-8166-2772\")),\nperson(given = \"Danielle\",\nfamily = \"Maeser\",\nrole = \"aut\",\nemail = \"maese005@umn.edu\",\ncomment = c(ORCID = \"0000-0002-3890-887X\")))", "Maintainer": "Robert Gruener ", "Description": "Allows for building drug response models using screening\ndata between bulk RNA-Seq and a drug response metric and two\nadditional tools for biomarker discovery that have been\ndeveloped by the Huang Laboratory at University of Minnesota.\nThere are 3 main functions within this package. (1)\ncalcPhenotype is used to build drug response models on RNA-Seq\ndata and impute them on any other RNA-Seq dataset given to the\nmodel. (2) GLDS is used to calculate the general level of drug\nsensitivity, which can improve biomarker discovery. (3) IDWAS\ncan take the results from calcPhenotype and link the imputed\nresponse back to available genomic (mutation and CNV\nalterations) to identify biomarkers. Each of these functions\ncomes from a paper from the Huang research laboratory. Below\ngives the relevant paper for each function. calcPhenotype -\nGeeleher et al, Clinical drug response can be predicted using\nbaseline gene expression levels and in vitro drug sensitivity\nin cell lines. GLDS - Geeleher et al, Cancer biomarker\ndiscovery is improved by accounting for variability in general\nlevels of drug sensitivity in pre-clinical models. IDWAS -\nGeeleher et al, Discovering novel pharmacogenomic biomarkers by\nimputing drug response in cancer patients from large genomics\nstudies.", "License": "GPL-2", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "biocViews": "sva, limma, stringr, biomaRt, genefilter, GenomicFeatures,\ngenefilter, TCGAbiolinks, BiocGenerics, GenomicRanges, IRanges,\nS4Vectors", "Additional_repositories": "https://bioconductor.org/packages/release/data/annotation", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Config/pak/sysreqs": "cmake make libgsl0-dev libbz2-dev libicu-dev\nliblzma-dev libpng-dev libxml2-dev libssl-dev xz-utils\nzlib1g-dev", "Repository": "https://huanglabumn.r-universe.dev", "Date/Publication": "2026-06-13 15:58:48 UTC", "RemoteUrl": "https://github.com/huanglabumn/oncopredict", "RemoteRef": "HEAD", "RemoteSha": "c16c1ffaffdd855f4ada4c83a3948e5c16b618c5", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-30 09:27:40 UTC", "User": "root" }, "Author": "Robert Gruener [aut, cre] (ORCID:\n),\nDanielle Maeser [aut] (ORCID: )", "MD5sum": "17cbd3f803a3f5eeeba4457aea6844ec", "_user": "huanglabumn", "_type": "src", "_file": "oncoPredict_1.3.tar.gz", "_fileid": "39bef2a4284b5ae0f27b3d35f04b62db1f1ae60aba99e0f9b15c41a7603fbf46", "_filesize": 2554765, "_sha256": "39bef2a4284b5ae0f27b3d35f04b62db1f1ae60aba99e0f9b15c41a7603fbf46", "_created": "2026-06-30T09:27:40.000Z", "_published": "2026-06-30T09:35:50.830Z", "_distro": "resolute", "_jobs": [ { "job": 84256510017, "time": 418, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7976570912" }, { "job": 84256509967, "time": 411, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "7976568482" }, { "job": 84256509962, "time": 410, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7976552132" }, { "job": 84256509961, "time": 278, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "7976505711" }, { "job": 84254944371, "time": 488, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "7976405642" }, { "job": 84256509969, "time": 241, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7976501842" }, { "job": 84256510030, "time": 381, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7976557232" }, { "job": 84256510072, "time": 313, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7976530043" }, { "job": 84256509980, "time": 310, "config": "windows-release", "r": "4.6.1", "check": "OK", "artifact": "7976528865" } ], "_buildurl": "https://github.com/r-universe/huanglabumn/actions/runs/28433863881", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/huanglabumn/oncopredict", "_commit": { "id": "c16c1ffaffdd855f4ada4c83a3948e5c16b618c5", "author": "HuangLabUMN <103966623+HuangLabUMN@users.noreply.github.com>", "committer": "GitHub ", "message": "Merge pull request #11 from RFGruener/main\n\nFixed additional formatting issues for CRAN", "time": 1781366328 }, "_maintainer": { "name": "Robert Gruener", "email": "rgruener@umn.edu", "login": "rfgruener", "description": "Post-Doctoral Fellow at the University of Minnesota in the lab of Stephanie Huang. 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