{
  "_id": "6a2141cacd65a98ecbd2a8b1",
  "Package": "SNPfiltR",
  "Title": "Interactively Filter SNP Datasets",
  "Version": "1.0.7",
  "Authors@R": "person(given = \"Devon\",\nfamily = \"DeRaad\",\nrole = c(\"aut\", \"cre\"),\nemail = \"devonderaad@gmail.com\",\ncomment = c(ORCID = \"0000-0003-3105-985X\"))",
  "Description": "Is designed to interactively and reproducibly visualize\nand filter SNP (single-nucleotide polymorphism) datasets. This\nR-based implementation of SNP and genotype filters facilitates\nan interactive and iterative SNP filtering pipeline, which can\nbe documented reproducibly via 'rmarkdown'. 'SNPfiltR' contains\nfunctions for visualizing various quality and missing data\nmetrics for a SNP dataset, and then filtering the dataset based\non user specified cutoffs. All functions take 'vcfR' objects as\ninput, which can easily be generated by reading standard vcf\n(variant call format) files into R using the R package 'vcfR'\nauthored by Knaus and Grünwald (2017)\n<doi:10.1111/1755-0998.12549>. Each 'SNPfiltR' function can\nreturn a newly filtered 'vcfR' object, which can then be\nwritten to a local directory in standard vcf format using the\n'vcfR' package, for downstream population genetic and\nphylogenetic analyses.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
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  "Packaged": {
    "Date": "2026-06-04 09:10:50 UTC",
    "User": "root"
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  "Author": "Devon DeRaad [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-3105-985X>)",
  "Maintainer": "Devon DeRaad <devonderaad@gmail.com>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2025-09-04 06:40:39 UTC",
  "RemoteUrl": "https://github.com/cran/SNPfiltR",
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    "author": "Devon DeRaad <devonderaad@gmail.com>",
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    "message": "version 1.0.7\n",
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    "email": "devonderaad@gmail.com",
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  "_assets": [
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      "date": "2021-10-28"
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      "date": "2022-01-25"
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      "date": "2022-04-16"
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      "date": "2023-03-17"
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    "assess_missing_data_tsne",
    "distance_thin",
    "filter_allele_balance",
    "filter_biallelic",
    "hard_filter",
    "max_depth",
    "min_mac",
    "missing_by_sample",
    "missing_by_snp"
  ],
  "_datasets": [
    {
      "name": "popmap",
      "title": "Popmap for example scrub-jay vcfR file",
      "object": "popmap",
      "class": [
        "data.frame"
      ],
      "fields": [
        "id",
        "pop"
      ],
      "rows": 20,
      "table": true,
      "tojson": true
    },
    {
      "name": "vcfR.example",
      "title": "Example scrub-jay vcfR file",
      "object": "vcfR.example",
      "class": [
        "vcfR"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    }
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  "_help": [
    {
      "page": "assess_missing_data_pca",
      "title": "Vizualise how missing data thresholds affect sample clustering",
      "topics": [
        "assess_missing_data_pca"
      ]
    },
    {
      "page": "assess_missing_data_tsne",
      "title": "Vizualise how missing data thresholds affect sample clustering",
      "topics": [
        "assess_missing_data_tsne"
      ]
    },
    {
      "page": "distance_thin",
      "title": "Filter a vcf file based on distance between SNPs on a given scaffold",
      "topics": [
        "distance_thin"
      ]
    },
    {
      "page": "filter_allele_balance",
      "title": "Filter out heterozygous genotypes failing an allele balance check",
      "topics": [
        "filter_allele_balance"
      ]
    },
    {
      "page": "filter_biallelic",
      "title": "Remove SNPs with more than two alleles",
      "topics": [
        "filter_biallelic"
      ]
    },
    {
      "page": "hard_filter",
      "title": "Hard filter a vcf file by depth and genotype quality (gq)",
      "topics": [
        "hard_filter"
      ]
    },
    {
      "page": "max_depth",
      "title": "Vizualise and filter based on mean depth across all called SNPs",
      "topics": [
        "max_depth"
      ]
    },
    {
      "page": "min_mac",
      "title": "Vizualise, filter based on Minor Allele Count (MAC)",
      "topics": [
        "min_mac"
      ]
    },
    {
      "page": "missing_by_sample",
      "title": "Vizualise missing data per sample, remove samples above a missing data cutoff",
      "topics": [
        "missing_by_sample"
      ]
    },
    {
      "page": "missing_by_snp",
      "title": "Vizualise missing data per SNP, remove SNPs above a missing data cutoff",
      "topics": [
        "missing_by_snp"
      ]
    },
    {
      "page": "popmap",
      "title": "Popmap for example scrub-jay vcfR file",
      "topics": [
        "popmap"
      ]
    },
    {
      "page": "SNPfiltR",
      "title": "SNPfiltR: A package for interactively visualizing and filtering SNP datasets",
      "topics": [
        "SNPfiltR"
      ]
    },
    {
      "page": "vcfR.example",
      "title": "Example scrub-jay vcfR file",
      "topics": [
        "vcfR.example"
      ]
    }
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      "filename": "reproducible-vignette.html",
      "title": "reproducible-vignette",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Optional Step 0:",
        "Step 1: read in vcf file as 'vcfR' object",
        "Step 2: quality filtering",
        "Note:",
        "Step 3: set missing data per sample cutoff",
        "Set arbitrary cutoff for missing data allowed per sample.",
        "Step 4: set missing data per SNP cutoff",
        "Set arbitrary cutoff for missing data allowed per SNP.",
        "Step 5: quality unaware filters",
        "Step 6: write out files for downstream analysis"
      ],
      "created": "2021-10-28 17:50:02",
      "modified": "2025-09-04 06:40:39",
      "commits": 3
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