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  "Title": "Keen and Reliable Interface Subroutines for Bioinformatic\nAnalysis",
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  "Authors@R": "c(person(given = \"Kridsadakorn\", family = \"Chaichoompu\", email = \"kridsadakorn@biostatgen.org\", role = c(\"aut\", \"cre\")),person(given = \"Kristel\", family = 'Van Steen', role = \"aut\"),person(given = \"Fentaw\", family = \"Abegaz\", role = \"aut\"),person(given = \"Sissades\", family = \"Tongsima\", role = \"aut\"),person(given = \"Philip\", family = \"James Shaw\", role = \"aut\"),person(given = \"Anavaj\", family = \"Sakuntabhai\", role = \"aut\"),person(given = \"Luisa\", family = \"Pereira\", role = \"aut\"))",
  "Description": "Provides useful functions which are needed for\nbioinformatic analysis such as calculating linear principal\ncomponents from numeric data and Single-nucleotide polymorphism\n(SNP) dataset, calculating fixation index (Fst) using Hudson\nmethod, creating scatter plots in 3 views, handling with PLINK\nbinary file format, detecting rough structures and outliers\nusing unsupervised clustering, and calculating matrix\nmultiplication in the faster way for big data.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "RoxygenNote": "7.1.1",
  "BugReports": "https://gitlab.com/kris.ccp/kris/-/issues",
  "URL": "https://gitlab.com/kris.ccp/kris",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-09-30 10:02:11 UTC",
    "User": "root"
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  "Author": "Kridsadakorn Chaichoompu [aut, cre], Kristel Van Steen [aut],\nFentaw Abegaz [aut], Sissades Tongsima [aut], Philip James Shaw\n[aut], Anavaj Sakuntabhai [aut], Luisa Pereira [aut]",
  "Maintainer": "Kridsadakorn Chaichoompu <kridsadakorn@biostatgen.org>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2021-01-21 11:10:02 UTC",
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    "fst.hudson",
    "plot3views",
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      "tojson": true
    }
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      "title": "Calculate linear principal component analysis (PCA) from numeric data and Single-nucleotide polymorphism (SNP) dataset",
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      ]
    },
    {
      "page": "cal.pc.projection",
      "title": "Calculate linear principal component analysis (PCA) with a projection method for Single-nucleotide polymorphism (SNP) dataset.",
      "topics": [
        "cal.pc.projection"
      ]
    },
    {
      "page": "fst.each.snp.hudson",
      "title": "Calculate the fixation index (Fst) for all SNPs between two groups of individuals from Single-nucleotide polymorphism (SNP)",
      "topics": [
        "fst.each.snp.hudson"
      ]
    },
    {
      "page": "fst.hudson",
      "title": "Calculate the average fixation index (Fst) between two groups of individuals from Single-nucleotide polymorphism (SNP)",
      "topics": [
        "fst.hudson"
      ]
    },
    {
      "page": "plot3views",
      "title": "Create scatter plots in three views.",
      "topics": [
        "plot3views"
      ]
    },
    {
      "page": "read.bed",
      "title": "Read the binary PLINK format (BED, BIM, and FAM)",
      "topics": [
        "read.bed"
      ]
    },
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      "page": "replace.missing",
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      ]
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      "page": "rubikclust",
      "title": "Unsupervised clustering to detect rough structures and outliers.",
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        "rubikclust"
      ]
    },
    {
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      "topics": [
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    },
    {
      "page": "simsnp",
      "title": "Synthetic dataset containing single nucleotide polymorphisms (SNP)",
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      "page": "write.bed",
      "title": "Write a list of SNP object to the binary PLINK format (BED, BIM, and FAM)",
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      ]
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      "page": "xxt",
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      ]
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