{ "_id": "6a1ae91d1d7bb097a09f27ae", "Package": "PAA", "Version": "1.47.0", "Title": "PAA (Protein Array Analyzer)", "Authors@R": "c(person(\"Michael\", \"Turewicz\", role=c(\"aut\", \"cre\"),\nemail=\"michael.turewicz@rub.de\"),\nperson(\"Martin\", \"Eisenacher\", role=c(\"ctb\", \"cre\"),\nemail=\"martin.eisenacher@rub.de\"))", "Author": "Michael Turewicz [aut, cre], Martin Eisenacher [ctb, cre]", "Maintainer": "Michael Turewicz , Martin\nEisenacher ", "Description": "PAA imports single color (protein) microarray data that\nhas been saved in gpr file format - esp. ProtoArray data. After\npreprocessing (background correction, batch filtering,\nnormalization) univariate feature preselection is performed\n(e.g., using the \"minimum M statistic\" approach - hereinafter\nreferred to as \"mMs\"). Subsequently, a multivariate feature\nselection is conducted to discover biomarker candidates.\nTherefore, either a frequency-based backwards elimination\naproach or ensemble feature selection can be used. PAA provides\na complete toolbox of analysis tools including several\ndifferent plots for results examination and evaluation.", "License": "BSD_3_clause + file LICENSE", "URL": "http://www.ruhr-uni-bochum.de/mpc/software/PAA/", "SystemRequirements": "C++ software package Random Jungle", "biocViews": "Classification, Microarray, OneChannel, Proteomics", "Config/pak/sysreqs": "libglpk-dev libpng-dev libxml2-dev libssl-dev\nzlib1g-dev", "Repository": "https://bioc.r-universe.dev", "Date/Publication": "2026-04-28 12:39:56 UTC", "RemoteUrl": "https://github.com/bioc/PAA", "RemoteRef": "HEAD", "RemoteSha": "413ee068d682fdc5e67e9d8a4c8cbde1c35c2193", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-30 09:37:35 UTC", "User": "root" }, "MD5sum": "00a8806cc95b29134d87d9803678043f", "_user": "bioc", "_type": "src", "_file": "PAA_1.47.0.tar.gz", "_fileid": "29ccdce25a0e9c27a3c3f0b8a53bb5c70b62b9ba918f84f5eb11c478bfd94374", "_filesize": 4516526, "_sha256": 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