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  "Title": "Maximum rank reproducibility",
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  "Date": "2021-05-10",
  "Authors@R": "c(person(\"Tusharkanti\", \"Ghosh\",\nemail = \"tusharkantighosh30@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Max\", \"McGrath\",\nrole = c(\"aut\")),\nperson(\"Daisy\", \"Philtron\",\nrole = c(\"aut\")),\nperson(\"Katerina\", \"Kechris\",\nrole = c(\"aut\")),\nperson(\"Debashis\", \"Ghosh\",\nrole = c(\"aut\", \"cph\")))",
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  "Description": "marr (Maximum Rank Reproducibility) is a nonparametric\napproach that detects reproducible signals using a maximal rank\nstatistic for high-dimensional biological data. In this R\npackage, we implement functions that measures the\nreproducibility of features per sample pair and sample pairs\nper feature in high-dimensional biological replicate\nexperiments. The user-friendly plot functions in this package\nalso plot histograms of the reproducibility of features per\nsample pair and sample pairs per feature. Furthermore, our\napproach also allows the users to select optimal filtering\nthreshold values for the identification of reproducible\nfeatures and sample pairs based on output visualization checks\n(histograms). This package also provides the subset of data\nfiltered by reproducible features and/or sample pairs.",
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