{
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  "Package": "diffee",
  "Version": "1.1.0",
  "Date": "2018-07-03",
  "Title": "Fast and Scalable Learning of Sparse Changes in High-Dimensional\nGaussian Graphical Model Structure",
  "Authors@R": "c(person(\"Beilun\", \"Wang\", role = c(\"aut\", \"cre\"), email = \"bw4mw@virginia.edu\"), person(\"Yanjun\", \"Qi\", role = \"aut\", email = \"yanjun@virginia.edu\"),person(\"Zhaoyang\", \"Wang\", role = c(\"aut\"), email = \"zw4dn@virginia.edu\"))",
  "Author": "Beilun Wang [aut, cre], Yanjun Qi [aut], Zhaoyang Wang [aut]",
  "Maintainer": "Beilun Wang <bw4mw@virginia.edu>",
  "Description": "This is an R implementation of Fast and Scalable Learning\nof Sparse Changes in High-Dimensional Gaussian Graphical Model\nStructure (DIFFEE). The DIFFEE algorithm can be used to fast\nestimate the differential network between two related datasets.\nFor instance, it can identify differential gene network from\ndatasets of case and control. By performing data-driven network\ninference from two high-dimensional data sets, this tool can\nhelp users effectively translate two aggregated data blocks\ninto knowledge of the changes among entities between two\nGaussian Graphical Model. Please run demo(diffeeDemo) to learn\nthe basic functions provided by this package. For further\ndetails, please read the original paper: Beilun Wang, Arshdeep\nSekhon, Yanjun Qi (2018) <arXiv:1710.11223>.",
  "License": "GPL-2",
  "URL": "https://github.com/QData/DIFFEE",
  "BugReports": "https://github.com/QData/DIFFEE",
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  "Repository": "https://blw921.r-universe.dev",
  "Date/Publication": "2018-07-03 18:50:03 UTC",
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      "title": "estimating DIFFerential networks via an Elementary Estimator under a high-dimensional situation",
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      "page": "diffee",
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