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  "Package": "ClusterSignificance",
  "Title": "The ClusterSignificance package provides tools to assess if\nclass clusters in dimensionality reduced data representations\nhave a separation different from permuted data",
  "Version": "1.41.0",
  "Authors@R": "c(\nperson(\"Jason T.\", \"Serviss\", email = \"Jason.serviss@ki.se\", role = c(\"aut\", \"cre\"), comment = c(ORCID = 0000-0002-5778-7014)),\nperson(\"Jesper R.\", \"Gadin\", email = \"Jesper.gadin@ki.se\", role = c(\"aut\"))\n)",
  "Author": "Jason T. Serviss [aut, cre], Jesper R. Gadin [aut]",
  "Maintainer": "Jason T Serviss <jason.serviss@ki.se>",
  "Description": "The ClusterSignificance package provides tools to assess\nif class clusters in dimensionality reduced data\nrepresentations have a separation different from permuted data.\nThe term class clusters here refers to, clusters of points\nrepresenting known classes in the data. This is particularly\nuseful to determine if a subset of the variables, e.g. genes in\na specific pathway, alone can separate samples into these\nestablished classes. ClusterSignificance accomplishes this by,\nprojecting all points onto a one dimensional line. Cluster\nseparations are then scored and the probability of the seen\nseparation being due to chance is evaluated using a permutation\nmethod.",
  "URL": "https://github.com/jasonserviss/ClusterSignificance/",
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  "Date/Publication": "2026-04-28 12:43:24 UTC",
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        "ClusterSignificance"
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        "ClassifiedPoints",
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        "classify",
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