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  "Date": "2005-09-02",
  "Title": "A Genotype Calling Algorithm for Affymetrix SNP Arrays",
  "Author": "Nusrat Rabbee <nrabbee@post.harvard.edu>, Gary Wong\n<wongg62@berkeley.edu>",
  "Maintainer": "Nusrat Rabbee <nrabbee@post.harvard.edu>",
  "Description": "A classification algorithm, based on a multi-chip,\nmulti-SNP approach for Affymetrix SNP arrays. Using a large\ntraining sample where the genotype labels are known, this\naglorithm will obtain more accurate classification results on\nnew data. RLMM is based on a robust, linear model and uses the\nMahalanobis distance for classification. The chip-to-chip\nnon-biological variation is removed through normalization. This\nmodel-based algorithm captures the similarities across genotype\ngroups and probes, as well as thousands other SNPs for accurate\nclassification. NOTE: 100K-Xba only at for now.",
  "License": "LGPL (>= 2)",
  "SystemRequirements": "Internal files Xba.CQV, Xba.regions (or other\nregions file)",
  "URL": "http://www.stat.berkeley.edu/users/nrabbee/RLMM",
  "biocViews": "Microarray, OneChannel, SNP, GeneticVariability",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:31:25 UTC",
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    "message": "bump x.y.z version to odd y following creation of RELEASE_3_23 branch\n",
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    "type": "organization",
    "name": "Bioconductor",
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      "title": "Classification of SNPs based on theta estimates",
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      "engine": "utils::Sweave",
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        "Instructions for Genotyping Affymetrix Mapping 100K array - Xba set",
        "Where can I learn more about RLMM?",
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        "References"
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