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  "Version": "1.5-3",
  "Date": "2024-03-26",
  "Title": "PLS Analyses for Genomics",
  "Author": "Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>,\nGhislain Durif <gd.dev@libertymail.net>, Sophie Lambert-Lacroix\n<sophie.lambert-lacroix@univ-grenoble-alpes.fr>, Julie Peyre\n<Julie.Peyre@univ-grenoble-alpes.fr>, and Korbinian Strimmer\n<k.strimmer@imperial.ac.uk>.",
  "Maintainer": "Ghislain Durif <gd.dev@libertymail.net>",
  "Encoding": "UTF-8",
  "Description": "Routines for PLS-based genomic analyses, implementing PLS\nmethods for classification with microarray data and prediction\nof transcription factor activities from combined ChIP-chip\nanalysis. The >=1.2-1 versions include two new classification\nmethods for microarray data: GSIM and Ridge PLS. The >=1.3\nversions includes a new classification method combining\nvariable selection and compression in logistic regression\ncontext: logit-SPLS; and an adaptive version of the sparse PLS.",
  "License": "GPL (>= 2)",
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  "BugReports": "https://github.com/gdurif/plsgenomics/issues",
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    "logit.pls.cv",
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    "logit.spls.aux",
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    "m.rirls.spls.stab",
    "m.rirls.spls.tune",
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    "mrpls",
    "mrpls.cv",
    "mrplsaux",
    "multinom.spls",
    "multinom.spls.aux",
    "multinom.spls.cv",
    "multinom.spls.stab",
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    "pls.regression",
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    "rirls.spls.tune",
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    "sample.cont",
    "sample.multinom",
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    "spls.adapt.tune",
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    "standard.simpls",
    "TFA.estimate",
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    "unitr.simpls",
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    "ust.adapt",
    "variable.selection",
    "wirrls",
    "wpls"
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      "tojson": true
    },
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      "class": [
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      "table": false,
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      "object": "SRBCT",
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      "class": [
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      ],
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      "tojson": true
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      "title": "Gene expression data from Alon et al. (1999)",
      "topics": [
        "Colon"
      ]
    },
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      "title": "Ecoli gene expression and connectivity data from Kao et al. (2003)",
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      "title": "Gene expression data from Golub et al. (1999)",
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    },
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      "title": "Determination of the ridge regularization parameter and the number of PLS components to be used for classification with RPLS for categorical data",
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      "topics": [
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    },
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        "m.rirls.spls.stab",
        "m.rirls.spls.tune",
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