{
  "_id": "6a1a79aa1d7bb097a09d33c3",
  "Package": "LEA",
  "Title": "LEA: an R package for Landscape and Ecological Association\nStudies",
  "Version": "3.25.0",
  "Date": "2025-11-3",
  "Author": "Eric Frichot <eric.frichot@gmail.com>, Olivier Francois\n<olivier.francois@grenoble-inp.fr>, Clement Gain\n<clement.gain@univ-grenoble-alpes.fr>",
  "Maintainer": "Olivier Francois <olivier.francois@grenoble-inp.fr>",
  "Description": "LEA is an R package dedicated to population genomics,\nlandscape genomics and genotype-environment association tests.\nLEA can run analyses of population structure and genome-wide\ntests for local adaptation, and also performs imputation of\nmissing genotypes. The package includes statistical methods for\nestimating ancestry coefficients from large genotypic matrices\nand for evaluating the number of ancestral populations (snmf).\nIt performs statistical tests using latent factor mixed models\nfor identifying genetic polymorphisms that exhibit association\nwith environmental gradients or phenotypic traits (lfmm2). In\naddition, LEA computes values of genetic offset statistics\nbased on new or predicted environments (genetic.gap,\ngenetic.offset). LEA is mainly based on optimized programs that\ncan scale with the dimensions of large data sets.",
  "License": "GPL-3",
  "biocViews": "Software, Statistical Method, Clustering, Regression",
  "URL": "http://membres-timc.imag.fr/Olivier.Francois/lea.html",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-05-30 05:26:14 UTC",
    "User": "root"
  },
  "VignetteBuilder": "knitr",
  "RoxygenNote": "6.0.1",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:40:47 UTC",
  "RemoteUrl": "https://github.com/bioc/LEA",
  "RemoteRef": "HEAD",
  "RemoteSha": "89a169585b63bf4b1a6672262f5ebe31e9a0601d",
  "MD5sum": "7701d43c36371a4da22fe3943f993c75",
  "_user": "bioc",
  "_type": "src",
  "_file": "LEA_3.25.0.tar.gz",
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  "_created": "2026-05-30T05:26:14.000Z",
  "_published": "2026-05-30T05:46:18.773Z",
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  "_buildurl": "https://github.com/r-universe/bioc/actions/runs/26675570827",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/bioc/LEA",
  "_commit": {
    "id": "89a169585b63bf4b1a6672262f5ebe31e9a0601d",
    "author": "A Wokaty <andres.wokaty@sph.cuny.edu>",
    "committer": "A Wokaty <andres.wokaty@sph.cuny.edu>",
    "message": "bump x.y.z version to odd y following creation of RELEASE_3_23 branch\n",
    "time": 1777380047
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  "_maintainer": {
    "name": "Olivier Francois",
    "email": "olivier.francois@grenoble-inp.fr"
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  "_distro": "noble",
  "_registered": true,
  "_dependencies": [
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      "package": "R",
      "version": ">= 3.3.0",
      "role": "Depends"
    },
    {
      "package": "methods",
      "role": "Depends"
    },
    {
      "package": "stats",
      "role": "Depends"
    },
    {
      "package": "utils",
      "role": "Depends"
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    {
      "package": "graphics",
      "role": "Depends"
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      "role": "Suggests"
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  "_owner": "bioc",
  "_selfowned": true,
  "_usedby": 3,
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      "n": 2
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  ],
  "_tags": [],
  "_bioc": [
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      "version": "3.25.0",
      "bioc": "3.24"
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    {
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      "version": "3.24.0",
      "bioc": "3.23"
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  "_topics": [
    "software",
    "statistical method",
    "clustering",
    "regression",
    "openblas"
  ],
  "_userbio": {
    "uuid": 2286807,
    "type": "organization",
    "name": "Bioconductor",
    "description": "Software for the analysis and comprehension of high-throughput genomic data"
  },
  "_downloads": {
    "count": 1271,
    "source": "https://www.bioconductor.org/packages/stats/bioc/LEA"
  },
  "_mentions": 139,
  "_searchresults": 732,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/LEA.html",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "manual.pdf"
  ],
  "_realowner": "bioc",
  "_cranurl": false,
  "_exports": [
    "ancestrymap2geno",
    "ancestrymap2lfmm",
    "barchart",
    "combine.lfmmProject",
    "combine.snmfProject",
    "create.dataset",
    "cross.entropy",
    "cross.entropy.estimation",
    "export.lfmmProject",
    "export.pcaProject",
    "export.snmfProject",
    "G",
    "genetic.gap",
    "genetic.offset",
    "geno2lfmm",
    "import.lfmmProject",
    "import.pcaProject",
    "import.snmfProject",
    "impute",
    "lfmm",
    "lfmm.pvalues",
    "lfmm2",
    "lfmm2.test",
    "lfmm2geno",
    "load.lfmmProject",
    "load.pcaProject",
    "load.snmfProject",
    "pca",
    "ped2geno",
    "ped2lfmm",
    "plot",
    "Q",
    "read.env",
    "read.geno",
    "read.lfmm",
    "read.zscore",
    "remove.lfmmProject",
    "remove.pcaProject",
    "remove.snmfProject",
    "show",
    "snmf",
    "snmf.pvalues",
    "struct2geno",
    "summary",
    "tracy.widom",
    "vcf2geno",
    "vcf2lfmm",
    "write.env",
    "write.geno",
    "write.lfmm",
    "z.scores"
  ],
  "_datasets": [
    {
      "name": "example_ancestrymap",
      "title": "'ancestrymap' format description",
      "object": "example_ancestrymap",
      "file": "example_ancestrymap.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "SNP",
        "Ind",
        "Genotype"
      ],
      "rows": 12,
      "table": true,
      "tojson": true
    },
    {
      "name": "example_geno",
      "title": "Input file for 'snmf'",
      "object": "example_geno",
      "file": "example_geno.tab.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "data"
      ],
      "rows": 4,
      "table": true,
      "tojson": true
    },
    {
      "name": "example_lfmm",
      "title": "Input file for 'lfmm'",
      "object": "example_lfmm",
      "file": "example_lfmm.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "SNP1",
        "SNP2",
        "SNP3",
        "SNP4"
      ],
      "rows": 3,
      "table": true,
      "tojson": true
    },
    {
      "name": "example_ped",
      "title": "'ped' format description",
      "object": "example_ped",
      "file": "example_ped.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "i",
        "ind",
        "X1",
        "X2",
        "X3",
        "X4",
        "X5",
        "X6",
        "X7",
        "X8",
        "X9",
        "X10",
        "X11",
        "X12"
      ],
      "rows": 3,
      "table": true,
      "tojson": true
    },
    {
      "name": "example_vcf",
      "title": "'vcf' format description",
      "object": "example_vcf",
      "file": "example_vcf.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "CHROM",
        "POS",
        "ID",
        "REF",
        "ALT",
        "QUAL",
        "FILTER",
        "INFO",
        "FORMAT",
        "SAMPLE0",
        "SAMPLE1",
        "SAMPLE2"
      ],
      "rows": 6,
      "table": true,
      "tojson": true
    },
    {
      "name": "offset_example",
      "title": "Example data for genetic offset analysis",
      "object": "offset_example",
      "file": "offset_example.RData",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "Replop-package",
      "title": "LEA: an R package for Landscape and Ecological Associations studies.",
      "topics": [
        "LEA-package"
      ]
    },
    {
      "page": "ancestrymap",
      "title": "'ancestrymap' format description",
      "topics": [
        "ancestrymap",
        "example_ancestrymap"
      ]
    },
    {
      "page": "ancestrymap2geno",
      "title": "Convert from 'ancestrymap' to 'geno' format",
      "topics": [
        "ancestrymap2geno"
      ]
    },
    {
      "page": "ancestrymap2lfmm",
      "title": "Convert from 'ancestrymap' to 'lfmm' format",
      "topics": [
        "ancestrymap2lfmm"
      ]
    },
    {
      "page": "barchart",
      "title": "Bar plot representation of an snmf Q-matrix",
      "topics": [
        "barchart"
      ]
    },
    {
      "page": "main_createDataSet",
      "title": "create a data set with masked data",
      "topics": [
        "create.dataset"
      ]
    },
    {
      "page": "crossEntropy",
      "title": "Cross-entropy criterion for snmf runs",
      "topics": [
        "cross.entropy"
      ]
    },
    {
      "page": "main_crossEntropyEstimation",
      "title": "compute the cross-entropy criterion",
      "topics": [
        "cross.entropy.estimation"
      ]
    },
    {
      "page": "env",
      "title": "Environmental input file format for 'lfmm'",
      "topics": [
        "env"
      ]
    },
    {
      "page": "G",
      "title": "Ancestral allele frequencies from a snmf run",
      "topics": [
        "G"
      ]
    },
    {
      "page": "genetic_gap",
      "title": "Genetic gap: genetic offset and genetic distance between environments.",
      "topics": [
        "genetic.gap"
      ]
    },
    {
      "page": "genetic_offset",
      "title": "Genetic offset and genetic distance between environments.",
      "topics": [
        "genetic.offset"
      ]
    },
    {
      "page": "geno",
      "title": "Input file for 'snmf'",
      "topics": [
        "example_geno",
        "geno"
      ]
    },
    {
      "page": "geno2lfmm",
      "title": "Convert from 'geno' to 'lfmm' format",
      "topics": [
        "geno2lfmm"
      ]
    },
    {
      "page": "impute",
      "title": "Impute missing genotypes using an snmf object",
      "topics": [
        "impute"
      ]
    },
    {
      "page": "main_LFMM",
      "title": "Fitting Latent Factor Mixed Models (MCMC algorithm)",
      "topics": [
        "adjusted.pvalues,lfmmProject-method",
        "combine.lfmmProject",
        "combine.lfmmProject,character,character-method",
        "export.lfmmProject",
        "export.lfmmProject,character-method",
        "import.lfmmProject",
        "import.lfmmProject,character-method",
        "lfmm",
        "lfmm.pvalues,lfmmProject-method",
        "load.lfmmProject",
        "load.lfmmProject,character-method",
        "mlog10p.values,lfmmProject-method",
        "p.values,lfmmProject-method",
        "plot,lfmmProject-method",
        "remove.lfmmProject",
        "remove.lfmmProject,character-method",
        "show,lfmmClass-method",
        "show,lfmmProject-method",
        "summary,lfmmProject-method",
        "z.scores,lfmmProject-method"
      ]
    },
    {
      "page": "lfmm_data",
      "title": "Input file for 'lfmm'",
      "topics": [
        "example_lfmm",
        "lfmm.data"
      ]
    },
    {
      "page": "lfmm_pvalues",
      "title": "P-values from lfmm runs",
      "topics": [
        "lfmm.pvalues"
      ]
    },
    {
      "page": "lfmm2",
      "title": "Fitting Latent Factor Mixed Models (Least squares algorithm)",
      "topics": [
        "lfmm2",
        "lfmm2.test,lfmm2Class-method"
      ]
    },
    {
      "page": "lfmm2_test",
      "title": "P-values adjusted for latent factors computed by 'lfmm2'.",
      "topics": [
        "lfmm2.test"
      ]
    },
    {
      "page": "lfmm2geno",
      "title": "Convert from 'lfmm' to 'geno' format",
      "topics": [
        "lfmm2geno"
      ]
    },
    {
      "page": "offset_example",
      "title": "Example data for genetic offset analysis",
      "topics": [
        "offset_example"
      ]
    },
    {
      "page": "main_pca",
      "title": "Principal Component Analysis",
      "topics": [
        "$,pcaProject-method",
        "eigenvalues",
        "eigenvalues,pcaProject-method",
        "eigenvectors",
        "eigenvectors,pcaProject-method",
        "export.pcaProject",
        "export.pcaProject,character-method",
        "import.pcaProject",
        "import.pcaProject,character-method",
        "load.pcaProject",
        "load.pcaProject,character-method",
        "pca",
        "plot,pcaProject-method",
        "projections",
        "projections,pcaProject-method",
        "remove.pcaProject",
        "remove.pcaProject,character-method",
        "sdev",
        "sdev,pcaProject-method",
        "show,pcaProject-method",
        "summary,pcaProject-method",
        "tracy.widom,pcaProject-method"
      ]
    },
    {
      "page": "ped",
      "title": "'ped' format description",
      "topics": [
        "example_ped",
        "ped"
      ]
    },
    {
      "page": "ped2geno",
      "title": "Convert from 'ped' to 'geno' format",
      "topics": [
        "ped2geno"
      ]
    },
    {
      "page": "ped2lfmm",
      "title": "Convert from 'ped' to 'lfmm' format",
      "topics": [
        "ped2lfmm"
      ]
    },
    {
      "page": "Q",
      "title": "Admixture coefficients from a snmf run",
      "topics": [
        "Q"
      ]
    },
    {
      "page": "readEnv",
      "title": "Read environmental file in the 'env'format",
      "topics": [
        "read.env"
      ]
    },
    {
      "page": "readGeno",
      "title": "read a file in the 'geno' format",
      "topics": [
        "read.geno"
      ]
    },
    {
      "page": "readLfmm",
      "title": "Read files in the 'lfmm' format",
      "topics": [
        "read.lfmm"
      ]
    },
    {
      "page": "readZscore",
      "title": "Read the output files of 'lfmm'",
      "topics": [
        "read.zscore"
      ]
    },
    {
      "page": "main_sNMF",
      "title": "Estimates individual ancestry coefficients and ancestral allele frequencies.",
      "topics": [
        "barchart,snmfProject-method",
        "combine.snmfProject",
        "combine.snmfProject,character,character-method",
        "cross.entropy,snmfProject-method",
        "export.snmfProject",
        "export.snmfProject,character-method",
        "G,snmfProject-method",
        "import.snmfProject",
        "import.snmfProject,character-method",
        "impute,snmfProject-method",
        "load.snmfProject",
        "load.snmfProject,character-method",
        "plot,snmfProject-method",
        "Q,snmfProject-method",
        "remove.snmfProject",
        "remove.snmfProject,character-method",
        "show,snmfClass-method",
        "show,snmfProject-method",
        "snmf",
        "snmf.pvalues,snmfProject-method",
        "summary,snmfProject-method"
      ]
    },
    {
      "page": "snmf_pvalues",
      "title": "P-values for snmf population differentiation tests",
      "topics": [
        "snmf.pvalues"
      ]
    },
    {
      "page": "struct2geno",
      "title": "Conversion from the STRUCTURE format to the geno format.",
      "topics": [
        "struct2geno"
      ]
    },
    {
      "page": "main_tracyWidom",
      "title": "Tracy-Widom test for eigenvalues",
      "topics": [
        "tracy.widom"
      ]
    },
    {
      "page": "tutorial",
      "title": "Example tutorial data sets",
      "topics": [
        "tutorial"
      ]
    },
    {
      "page": "vcf",
      "title": "'vcf' format description",
      "topics": [
        "example_vcf",
        "vcf"
      ]
    },
    {
      "page": "vcf2geno",
      "title": "Convert from 'vcf' to 'geno' format",
      "topics": [
        "vcf2geno"
      ]
    },
    {
      "page": "vcf2lfmm",
      "title": "Convert from 'vcf' to 'lfmm' format",
      "topics": [
        "vcf2lfmm"
      ]
    },
    {
      "page": "writeEnv",
      "title": "Write files in the 'env' format",
      "topics": [
        "write.env"
      ]
    },
    {
      "page": "writeGeno",
      "title": "Write files in the 'geno' format",
      "topics": [
        "write.geno"
      ]
    },
    {
      "page": "writeLFMM",
      "title": "Write files in the 'lfmm' format",
      "topics": [
        "write.lfmm"
      ]
    },
    {
      "page": "zscores",
      "title": "z-scores from an lfmm run",
      "topics": [
        "lfmmClass-method",
        "z.scores"
      ]
    },
    {
      "page": "zscore",
      "title": "Output file format for 'lfmm'",
      "topics": [
        "zscore.format"
      ]
    }
  ],
  "_rundeps": [],
  "_sysdeps": [
    {
      "shlib": "liblapack",
      "package": "libopenblas0-pthread",
      "source": "openblas",
      "version": "0.3.26+ds-1ubuntu0.1",
      "name": "openblas",
      "homepage": "https://www.openblas.net/",
      "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)"
    }
  ],
  "_vignettes": [
    {
      "source": "LEA.Rnw",
      "filename": "LEA.pdf",
      "title": "LEA: An R Package for Landscape and Ecological Association Studies",
      "engine": "knitr::knitr",
      "headings": [],
      "created": "2015-03-13 17:25:56",
      "modified": "2023-02-27 12:18:11",
      "commits": 17
    }
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  "_score": 7.223929136715706,
  "_indexed": true,
  "_nocasepkg": "lea",
  "_universes": [
    "bioc"
  ],
  "_binaries": [
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      "os": "linux",
      "version": "3.25.0",
      "date": "2026-05-30T05:28:34.000Z",
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