{ "_id": "6a252f5d4b233be198395858", "Package": "modACDC", "Title": "Association of Covariance for Detecting Differential\nCo-Expression", "Version": "2.0.1", "Authors@R": "c(person(given = \"Katelyn\",\nfamily = \"Queen\",\nemail = \"kjqueen@usc.edu\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-8070-3042\")),\nperson(given = \"Joshua\",\nfamily = \"Millstein\", ,\nemail = \"joshua.millstein@usc.edu\",\nrole = c(\"aut\",\"cph\"),\ncomment = c(ORCID = \"0000-0001-7961-8943\")))", "Maintainer": "Katelyn Queen ", "Description": "A series of functions to implement association of\ncovariance for detecting differential co-expression (ACDC), a\nnovel approach for detection of differential co-expression that\nsimultaneously accommodates multiple phenotypes or exposures\nwith binary, ordinal, or continuous data types. Users can use\nthe default method which identifies modules by Partition or may\nsupply their own modules. Also included are functions to choose\nan information loss criterion (ILC) for Partition using\nOmicS-data-based Complex trait Analysis (OSCA) and Genome-wide\nComplex trait Analysis (GCTA). The manuscript describing these\nmethods is as follows: Queen K, Nguyen MN, Gilliland F, Chun S,\nRaby BA, Millstein J. \"ACDC: a general approach for detecting\nphenotype or exposure associated co-expression\" (2023)\n.", "License": "MIT + file LICENSE", "URL": "https://github.com/USCbiostats/ACDC", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.2.3", "Config/pak/sysreqs": "libicu-dev libx11-dev", "Repository": "https://uscbiostats.r-universe.dev", "Date/Publication": "2024-04-09 17:59:27 UTC", "RemoteUrl": "https://github.com/uscbiostats/acdc", "RemoteRef": "HEAD", "RemoteSha": "4d535285fc8394f0691f91d2a860ef4a14b85a8f", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-07 08:41:17 UTC", "User": "root" }, "Author": "Katelyn Queen [aut, cre, cph] (ORCID:\n),\nJoshua Millstein [aut, cph] (ORCID:\n)", "MD5sum": "0f9a5fc9941228919480b36f355f01b4", "_user": "uscbiostats", "_type": "src", "_file": "modACDC_2.0.1.tar.gz", "_fileid": 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