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  "Type": "Package",
  "Title": "Genome-Wide Association Study with SNP-Set Methods",
  "Version": "0.1.42",
  "Authors@R": "c(\nperson(\"Kosuke\", \"Hamazaki\", email = \"hamazaki@ut-biomet.org\", role = c(\"aut\", \"cre\")),\nperson(\"Hiroyoshi\", \"Iwata\", email = \"aiwata@mail.ecc.u-tokyo.ac.jp\", role = c(\"aut\", \"ctb\"))\n)",
  "Maintainer": "Kosuke Hamazaki <hamazaki@ut-biomet.org>",
  "Description": "By using 'RAINBOWR' (Reliable Association INference By\nOptimizing Weights with R), users can test multiple SNPs\n(Single Nucleotide Polymorphisms) simultaneously by\nkernel-based (SNP-set) methods. This package can also be\napplied to haplotype-based GWAS (Genome-Wide Association\nStudy). Users can test not only additive effects but also\ndominance and epistatic effects. In detail, please check our\npaper on PLOS Computational Biology: Kosuke Hamazaki and\nHiroyoshi Iwata (2020) <doi:10.1371/journal.pcbi.1007663>.",
  "License": "MIT + file LICENSE",
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  "Repository": "https://kosukehamazaki.r-universe.dev",
  "Date/Publication": "2026-10-13 09:32:04 UTC",
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  "Author": "Kosuke Hamazaki [aut, cre],\nHiroyoshi Iwata [aut, ctb]",
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    "message": "Update EMM3.cpp functions\n",
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  "_exports": [
    "adjustGRM",
    "calcGRM",
    "calcParamSE",
    "calcParamSE.cov",
    "CalcThreshold",
    "convertBlockList",
    "cumsumPos",
    "design.Z",
    "EM3.cov",
    "EM3.cpp",
    "EM3.general",
    "EM3.linker.cpp",
    "EMM.cpp",
    "EMM1.cpp",
    "EMM2.cpp",
    "estNetwork",
    "estPhylo",
    "genesetmap",
    "genetrait",
    "is.diag",
    "MAF.cut",
    "make.full",
    "manhattan",
    "manhattan.plus",
    "manhattan2",
    "manhattan3",
    "modify.data",
    "parallel.compute",
    "plotHaploNetwork",
    "plotPhyloTree",
    "qq",
    "RGWAS.epistasis",
    "RGWAS.multisnp",
    "RGWAS.multisnp.interaction",
    "RGWAS.normal",
    "RGWAS.normal.interaction",
    "RGWAS.twostep",
    "RGWAS.twostep.epi",
    "score.calc",
    "score.calc.epistasis.LR",
    "score.calc.epistasis.LR.MC",
    "score.calc.epistasis.score",
    "score.calc.epistasis.score.MC",
    "score.calc.int",
    "score.calc.int.MC",
    "score.calc.LR",
    "score.calc.LR.int",
    "score.calc.LR.int.MC",
    "score.calc.LR.MC",
    "score.calc.MC",
    "score.calc.score",
    "score.calc.score.MC",
    "score.cpp",
    "score.linker.cpp",
    "See",
    "spectralG.cpp",
    "SS_gwas",
    "welcome_to_RGWAS"
  ],
  "_datasets": [
    {
      "name": "Rice_Zhao_etal",
      "title": "Rice_Zhao_etal:",
      "object": "Rice_Zhao_etal",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "adjustGRM",
      "title": "Function to adjust genomic relationship matrix (GRM) with subpopulations",
      "topics": [
        "adjustGRM"
      ]
    },
    {
      "page": "calcGRM",
      "title": "Function to calculate genomic relationship matrix (GRM)",
      "topics": [
        "calcGRM"
      ]
    },
    {
      "page": "calcParamSE",
      "title": "Calculate Standard Errors for Variance Parameters",
      "topics": [
        "calcParamSE"
      ]
    },
    {
      "page": "calcParamSE.cov",
      "title": "Calculate Standard Errors for Variance and Correlation Parameters",
      "topics": [
        "calcParamSE.cov"
      ]
    },
    {
      "page": "CalcThreshold",
      "title": "Function to calculate threshold for GWAS",
      "topics": [
        "CalcThreshold"
      ]
    },
    {
      "page": "convertBlockList",
      "title": "Function to convert haplotype block list from PLINK to RAINBOWR format",
      "topics": [
        "convertBlockList"
      ]
    },
    {
      "page": "cumsumPos",
      "title": "Function to calculate cumulative position (beyond chromosome)",
      "topics": [
        "cumsumPos"
      ]
    },
    {
      "page": "design.Z",
      "title": "Function to generate design matrix (Z)",
      "topics": [
        "design.Z"
      ]
    },
    {
      "page": "EM3.cov",
      "title": "Equation of mixed model for multi-kernel considering covariance structure between kernels",
      "topics": [
        "EM3.cov"
      ]
    },
    {
      "page": "EM3.cpp",
      "title": "Equation of mixed model for multi-kernel (slow, general version)",
      "topics": [
        "EM3.cpp"
      ]
    },
    {
      "page": "EM3.general",
      "title": "Equation of mixed model for multi-kernel including using other packages (with other packages, much faster than EM3.cpp)",
      "topics": [
        "EM3.general"
      ]
    },
    {
      "page": "EM3.linker.cpp",
      "title": "Equation of mixed model for multi-kernel (fast, for limited cases)",
      "topics": [
        "EM3.linker.cpp"
      ]
    },
    {
      "page": "EM3.op",
      "title": "Equation of mixed model for multi-kernel using other packages (much faster than EM3.cpp)",
      "topics": [
        "EM3.op"
      ]
    },
    {
      "page": "EMM.cpp",
      "title": "Equation of mixed model for one kernel, a wrapper of two methods",
      "topics": [
        "EMM.cpp"
      ]
    },
    {
      "page": "EMM1.cpp",
      "title": "Equation of mixed model for one kernel, GEMMA-based method (inplemented by Rcpp)",
      "topics": [
        "EMM1.cpp"
      ]
    },
    {
      "page": "EMM2.cpp",
      "title": "Equation of mixed model for one kernel, EMMA-based method (inplemented by Rcpp)",
      "topics": [
        "EMM2.cpp"
      ]
    },
    {
      "page": "estNetwork",
      "title": "Function to estimate & plot haplotype network",
      "topics": [
        "estNetwork"
      ]
    },
    {
      "page": "estPhylo",
      "title": "Function to estimate & plot phylogenetic tree",
      "topics": [
        "estPhylo"
      ]
    },
    {
      "page": "genesetmap",
      "title": "Function to generate map for gene set",
      "topics": [
        "genesetmap"
      ]
    },
    {
      "page": "genetrait",
      "title": "Generate pseudo phenotypic values",
      "topics": [
        "genetrait"
      ]
    },
    {
      "page": "is.diag",
      "title": "Function to judge the square matrix whether it is diagonal matrix or not",
      "topics": [
        "is.diag"
      ]
    },
    {
      "page": "MAF.cut",
      "title": "Function to remove the minor alleles",
      "topics": [
        "MAF.cut"
      ]
    },
    {
      "page": "make.full",
      "title": "Change a matrix to full-rank matrix",
      "topics": [
        "make.full"
      ]
    },
    {
      "page": "manhattan",
      "title": "Draw manhattan plot",
      "topics": [
        "manhattan"
      ]
    },
    {
      "page": "manhattan.plus",
      "title": "Add points of -log10(p) corrected by kernel methods to manhattan plot",
      "topics": [
        "manhattan.plus"
      ]
    },
    {
      "page": "manhattan2",
      "title": "Draw manhattan plot (another method)",
      "topics": [
        "manhattan2"
      ]
    },
    {
      "page": "manhattan3",
      "title": "Draw the effects of epistasis (3d plot and 2d plot)",
      "topics": [
        "manhattan3"
      ]
    },
    {
      "page": "modify.data",
      "title": "Function to modify genotype and phenotype data to match",
      "topics": [
        "modify.data"
      ]
    },
    {
      "page": "parallel.compute",
      "title": "Function to parallelize computation with various methods",
      "topics": [
        "parallel.compute"
      ]
    },
    {
      "page": "plotHaploNetwork",
      "title": "Function to plot haplotype network from the estimated results",
      "topics": [
        "plotHaploNetwork"
      ]
    },
    {
      "page": "plotPhyloTree",
      "title": "Function to plot phylogenetic tree from the estimated results",
      "topics": [
        "plotPhyloTree"
      ]
    },
    {
      "page": "qq",
      "title": "Draw qq plot",
      "topics": [
        "qq"
      ]
    },
    {
      "page": "RAINBOWR",
      "title": "RAINBOWR: Perform Genome-Wide Asscoiation Study (GWAS) By Kernel-Based Methods",
      "topics": [
        "RAINBOWR-package",
        "RAINBOWR"
      ]
    },
    {
      "page": "RGWAS.epistasis",
      "title": "Check epistatic effects by kernel-based GWAS (genome-wide association studies)",
      "topics": [
        "RGWAS.epistasis"
      ]
    },
    {
      "page": "RGWAS.menu",
      "title": "Print the R code which you should perform for RAINBOWR GWAS",
      "topics": [
        "RGWAS.menu"
      ]
    },
    {
      "page": "RGWAS.multisnp",
      "title": "Testing multiple SNPs simultaneously for GWAS",
      "topics": [
        "RGWAS.multisnp"
      ]
    },
    {
      "page": "RGWAS.multisnp.interaction",
      "title": "Testing multiple SNPs and their interaction with some kernel simultaneously for GWAS",
      "topics": [
        "RGWAS.multisnp.interaction"
      ]
    },
    {
      "page": "RGWAS.normal",
      "title": "Perform normal GWAS (test each single SNP)",
      "topics": [
        "RGWAS.normal"
      ]
    },
    {
      "page": "RGWAS.normal.interaction",
      "title": "Perform normal GWAS including interaction (test each single SNP)",
      "topics": [
        "RGWAS.normal.interaction"
      ]
    },
    {
      "page": "RGWAS.twostep",
      "title": "Perform normal GWAS (genome-wide association studies) first, then perform SNP-set GWAS for relatively significant markers",
      "topics": [
        "RGWAS.twostep"
      ]
    },
    {
      "page": "RGWAS.twostep.epi",
      "title": "Perform normal GWAS (genome-wide association studies) first, then check epistatic effects for relatively significant markers",
      "topics": [
        "RGWAS.twostep.epi"
      ]
    },
    {
      "page": "Rice_geno_map",
      "title": "Physical map of rice genome",
      "topics": [
        "Rice_geno_map"
      ]
    },
    {
      "page": "Rice_geno_score",
      "title": "Marker genotype of rice genome",
      "topics": [
        "Rice_geno_score"
      ]
    },
    {
      "page": "Rice_haplo_block",
      "title": "Physical map of rice genome",
      "topics": [
        "Rice_haplo_block"
      ]
    },
    {
      "page": "Rice_pheno",
      "title": "Phenotype data of rice field trial",
      "topics": [
        "Rice_pheno"
      ]
    },
    {
      "page": "Rice_Zhao_etal",
      "title": "Rice_Zhao_etal:",
      "topics": [
        "Rice_Zhao_etal"
      ]
    },
    {
      "page": "score.calc",
      "title": "Calculate -log10(p) for single-SNP GWAS",
      "topics": [
        "score.calc"
      ]
    },
    {
      "page": "score.calc.epistasis.LR",
      "title": "Calculate -log10(p) of epistatic effects by LR test",
      "topics": [
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    {
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      "title": "Calculate -log10(p) of epistatic effects by LR test (multi-cores)",
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    {
      "page": "score.calc.epistasis.score",
      "title": "Calculate -log10(p) of epistatic effects with score test",
      "topics": [
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    {
      "page": "score.calc.epistasis.score.MC",
      "title": "Calculate -log10(p) of epistatic effects with score test (multi-cores)",
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    {
      "page": "score.calc.int",
      "title": "Calculate -log10(p) for single-SNP GWAS with interaction",
      "topics": [
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    },
    {
      "page": "score.calc.int.MC",
      "title": "Calculate -log10(p) for single-SNP GWAS with interaction (multi-cores)",
      "topics": [
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    {
      "page": "score.calc.LR",
      "title": "Calculate -log10(p) of each SNP-set by the LR test",
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      "page": "score.calc.LR.int",
      "title": "Calculate -log10(p) of each SNP-set and its interaction with kernels by the LR test",
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      "page": "score.calc.LR.int.MC",
      "title": "Calculate -log10(p) of each SNP-set and its interaction with kernels by the LR test (multi-cores)",
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    {
      "page": "score.calc.LR.MC",
      "title": "Calculate -log10(p) of each SNP-set by the LR test (multi-cores)",
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    {
      "page": "score.calc.MC",
      "title": "Calculate -log10(p) for single-SNP GWAS (multi-cores)",
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      "title": "Calculate -log10(p) of each SNP-set by the score test",
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    {
      "page": "SS_gwas",
      "title": "Calculate some summary statistics of GWAS (genome-wide association studies) for simulation study",
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      "source": "RAINBOWR.Rmd",
      "filename": "RAINBOWR.html",
      "title": "RAINBOWR: Reliable Association INference By Optimizing Weights with R",
      "author": "Kosuke Hamazaki (hamazaki@ut-biomet.org), Hiroyoshi Iwata",
      "engine": "knitr::rmarkdown",
      "headings": [
        "NOTE!!!!",
        "The paper for RAINBOWR has been published in PLOS Computational Biology (https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007663). If you use this RAINBOWR in your paper, please cite RAINBOWR as follows:",
        "The stable version for RAINBOWR package is now available at the CRAN (Comprehensive R Archive Network).",
        "Please check the change in RAINBOWR with the version update from NEWS.md.",
        "What is RAINBOWR",
        "Installation",
        "Usage",
        "Help",
        "References"
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      "created": "2019-10-21 04:30:11",
      "modified": "2022-01-31 14:06:07",
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