{
  "_id": "6a1fdc27b401979e73437e60",
  "Package": "RCM",
  "Type": "Package",
  "Title": "Fit row-column association models with the negative binomial\ndistribution for the microbiome",
  "Version": "1.29.0",
  "Authors@R": "c(person(given = \"Stijn\", family = \"Hawinkel\",\nemail = \"stijn.hawinkel@psb.ugent.be\",\nrole=c(\"cre\", \"aut\"), comment = c(ORCID = \"0000-0002-4501-5180\")))",
  "Description": "Combine ideas of log-linear analysis of contingency table,\nflexible response function estimation and empirical Bayes\ndispersion estimation for explorative visualization of\nmicrobiome datasets. The package includes unconstrained as well\nas constrained analysis. In addition, diagnostic plot to detect\nlack of fit are available.",
  "License": "GPL-2",
  "Encoding": "UTF-8",
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  "biocViews": "Metagenomics, DimensionReduction, Microbiome, Visualization",
  "BugReports": "https://github.com/CenterForStatistics-UGent/RCM/issues",
  "URL": "https://bioconductor.org/packages/release/bioc/vignettes/RCM/inst/doc/RCMvignette.html/",
  "Config/pak/sysreqs": "libglpk-dev libicu-dev libxml2-dev libssl-dev\nzlib1g-dev",
  "Repository": "https://bioc.r-universe.dev",
  "Date/Publication": "2026-04-28 12:49:21 UTC",
  "RemoteUrl": "https://github.com/bioc/RCM",
  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-03 07:40:13 UTC",
    "User": "root"
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  "Author": "Stijn Hawinkel [cre, aut] (ORCID:\n<https://orcid.org/0000-0002-4501-5180>)",
  "Maintainer": "Stijn Hawinkel <stijn.hawinkel@psb.ugent.be>",
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  "_created": "2026-06-03T07:40:13.000Z",
  "_published": "2026-06-03T07:47:51.918Z",
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    "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",
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    "email": "stijn.hawinkel@psb.ugent.be",
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      "package": "tensor",
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      "package": "MASS",
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    "microbiome",
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    "ordination",
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    "rcm"
  ],
  "_stars": 16,
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    "description": "Software for the analysis and comprehension of high-throughput genomic data"
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    "source": "https://www.bioconductor.org/packages/stats/bioc/RCM"
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  "_mentions": 15,
  "_devurl": "https://github.com/centerforstatistics-ugent/rcm",
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  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
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    "extra/NEWS.txt",
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    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
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  "_homeurl": "https://github.com/centerforstatistics-ugent/rcm",
  "_realowner": "bioc",
  "_cranurl": false,
  "_exports": [
    "addOrthProjection",
    "buildConfMat",
    "checkAlias",
    "extractCoord",
    "getDevianceRes",
    "inertia",
    "liks",
    "permanova",
    "plotRespFun",
    "RCM",
    "RCM_NB",
    "residualPlot"
  ],
  "_datasets": [
    {
      "name": "Zeller",
      "title": "Microbiomes of colorectal cancer patients and healthy controls",
      "object": "Zeller",
      "file": "Zeller.RData",
      "class": [
        "phyloseq"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    }
  ],
  "_help": [
    {
      "page": "addOrthProjection",
      "title": "This function adds orthogonal projections to a given plot",
      "topics": [
        "addOrthProjection"
      ]
    },
    {
      "page": "arrayprod",
      "title": "An auxiliary R function to 'array' multiply an array with a vector, kindly provided by Joris Meys",
      "topics": [
        "arrayprod"
      ]
    },
    {
      "page": "buildCentMat",
      "title": "A function to build a centering matrix based on a dataframe",
      "topics": [
        "buildCentMat"
      ]
    },
    {
      "page": "buildConfMat",
      "title": "A function to build the confounder matrices",
      "topics": [
        "buildConfMat"
      ]
    },
    {
      "page": "buildConfMat-character-method",
      "title": "buildConfMat.character",
      "topics": [
        "buildConfMat,character-method"
      ]
    },
    {
      "page": "buildConfMat-data.frame-method",
      "title": "buildConfMat.data.frame",
      "topics": [
        "buildConfMat,data.frame-method"
      ]
    },
    {
      "page": "buildCovMat",
      "title": "A function to build the covariate matrix of the constraints",
      "topics": [
        "buildCovMat"
      ]
    },
    {
      "page": "buildDesign",
      "title": "A function to build the design matrix",
      "topics": [
        "buildDesign"
      ]
    },
    {
      "page": "checkAlias",
      "title": "Check for alias structures in a dataframe, and throw an error when one is found",
      "topics": [
        "checkAlias"
      ]
    },
    {
      "page": "constrCorresp",
      "title": "Constrained correspondence analysis with adapted powers",
      "topics": [
        "constrCorresp"
      ]
    },
    {
      "page": "correctXMissingness",
      "title": "Replace missing entries in X by their expectation to set their contribution to the estimating equations to zero",
      "topics": [
        "correctXMissingness"
      ]
    },
    {
      "page": "deviances",
      "title": "A function to extract deviances for all dimension, including after filtering on confounders",
      "topics": [
        "deviances"
      ]
    },
    {
      "page": "dLR_nb",
      "title": "A function that returns the value of the partial derivative of the log-likelihood ratio to alpha, keeping the response functions fixed",
      "topics": [
        "dLR_nb"
      ]
    },
    {
      "page": "dNBabundsOld",
      "title": "A score function for the column components of the independence model (mean relative abundances)",
      "topics": [
        "dNBabundsOld"
      ]
    },
    {
      "page": "dNBlibSizes",
      "title": "A score function for the row components of the independence model (library sizes)",
      "topics": [
        "dNBlibSizes"
      ]
    },
    {
      "page": "dNBllcol_constr",
      "title": "The score function of the response function for 1 taxon at the time",
      "topics": [
        "dNBllcol_constr"
      ]
    },
    {
      "page": "dNBllcol_constr_noLab",
      "title": "The score function of the general response function",
      "topics": [
        "dNBllcol_constr_noLab"
      ]
    },
    {
      "page": "dNBllcolNP",
      "title": "Estimation of the parameters of a third degree GLM",
      "topics": [
        "dNBllcolNP"
      ]
    },
    {
      "page": "dNBllcolOld",
      "title": "A score function for the estimation of the column scores in an unconstrained RC(M) model",
      "topics": [
        "dNBllcolOld"
      ]
    },
    {
      "page": "dNBllrow",
      "title": "A score function of the NB for the row scores",
      "topics": [
        "dNBllrow"
      ]
    },
    {
      "page": "dNBpsis",
      "title": "A score function for the psi of a given dimension",
      "topics": [
        "dNBpsis"
      ]
    },
    {
      "page": "ellipseCoord",
      "title": "A function that returns the coordinates of an ellipse",
      "topics": [
        "ellipseCoord"
      ]
    },
    {
      "page": "estDisp",
      "title": "Estimate the overdispersion",
      "topics": [
        "estDisp"
      ]
    },
    {
      "page": "estNBparams",
      "title": "A function to estimate the taxon-wise NB-params",
      "topics": [
        "estNBparams"
      ]
    },
    {
      "page": "estNBparamsNoLab",
      "title": "A function to estimate the NB-params ignoring the taxon labels",
      "topics": [
        "estNBparamsNoLab"
      ]
    },
    {
      "page": "estNPresp",
      "title": "Estimate the taxon-wise response functions non-parametrically",
      "topics": [
        "estNPresp"
      ]
    },
    {
      "page": "extractCoord",
      "title": "A function to extract plotting coordinates, either for plot.RCM or to export to other plotting software",
      "topics": [
        "extractCoord"
      ]
    },
    {
      "page": "extractE",
      "title": "A function to extract a matrix of expected values for any dimension of the fit",
      "topics": [
        "extractE"
      ]
    },
    {
      "page": "filterConfounders",
      "title": "Filters out the effect of known confounders. This is done by fitting interactions of every taxon with the levels of the confounders. It returns a modified offset matrix for the remainder of the fitting procedure.",
      "topics": [
        "filterConfounders"
      ]
    },
    {
      "page": "getDevianceRes",
      "title": "A function to calculate the matrix of deviance residuals.",
      "topics": [
        "getDevianceRes"
      ]
    },
    {
      "page": "getDevMat",
      "title": "ACalculate the matrix of deviance residuals",
      "topics": [
        "getDevMat"
      ]
    },
    {
      "page": "getDistCoord",
      "title": "Get coordinates of a distance object of n observations for the provided indices",
      "topics": [
        "getDistCoord"
      ]
    },
    {
      "page": "getInflCol",
      "title": "A function to extract the influence for a given parameter index",
      "topics": [
        "getInflCol"
      ]
    },
    {
      "page": "getInflRow",
      "title": "Extract the influence of all observations on a given row score",
      "topics": [
        "getInflRow"
      ]
    },
    {
      "page": "getInt",
      "title": "Integrate the spline of an vgam object",
      "topics": [
        "getInt"
      ]
    },
    {
      "page": "getLogLik",
      "title": "Extract the logged likelihood of every count",
      "topics": [
        "getLogLik"
      ]
    },
    {
      "page": "getModelMat",
      "title": "A function to construct a model matrix of a certain degree",
      "topics": [
        "getModelMat"
      ]
    },
    {
      "page": "getRowMat",
      "title": "Return a matrix of row scores",
      "topics": [
        "getRowMat"
      ]
    },
    {
      "page": "GramSchmidt",
      "title": "Gram-Schmidt orthogonalization of vectors",
      "topics": [
        "GramSchmidt"
      ]
    },
    {
      "page": "heq_nb",
      "title": "Define linear equality constraints for env. gradient",
      "topics": [
        "heq_nb"
      ]
    },
    {
      "page": "heq_nb_jac",
      "title": "The jacobian of the linear equality constraints",
      "topics": [
        "heq_nb_jac"
      ]
    },
    {
      "page": "indentPlot",
      "title": "Functions to indent the plot to include the entire labels",
      "topics": [
        "indentPlot"
      ]
    },
    {
      "page": "inertia",
      "title": "Calculate the log-likelihoods of all possible models",
      "topics": [
        "inertia"
      ]
    },
    {
      "page": "JacCol_constr",
      "title": "Jacobian of the constrained analysis with linear response function.",
      "topics": [
        "JacCol_constr"
      ]
    },
    {
      "page": "JacCol_constr_noLab",
      "title": "The jacobian of the response function without taxon labels",
      "topics": [
        "JacCol_constr_noLab"
      ]
    },
    {
      "page": "liks",
      "title": "Calculate the log-likelihoods of all possible models",
      "topics": [
        "liks"
      ]
    },
    {
      "page": "LR_nb",
      "title": "Get the value of the log-likelihood ratio of alpha",
      "topics": [
        "LR_nb"
      ]
    },
    {
      "page": "LR_nb_Jac",
      "title": "A function that returns the Jacobian of the likelihood ratio",
      "topics": [
        "LR_nb_Jac"
      ]
    },
    {
      "page": "NBalphaInfl",
      "title": "Calculate the components of the influence functions",
      "topics": [
        "NBalphaInfl"
      ]
    },
    {
      "page": "NBcolInfl",
      "title": "The influence function for the column scores",
      "topics": [
        "NBcolInfl"
      ]
    },
    {
      "page": "NBjacobianAbundsOld",
      "title": "Jacobian for the column components of the independence model",
      "topics": [
        "NBjacobianAbundsOld"
      ]
    },
    {
      "page": "NBjacobianColNP",
      "title": "Jacobian function for the estimation of a third degree GLM",
      "topics": [
        "NBjacobianColNP"
      ]
    },
    {
      "page": "NBjacobianColOld",
      "title": "Jacobian for the estimation of the column scores",
      "topics": [
        "NBjacobianColOld"
      ]
    },
    {
      "page": "NBjacobianLibSizes",
      "title": "Jacobian for the raw components of the independence model",
      "topics": [
        "NBjacobianLibSizes"
      ]
    },
    {
      "page": "NBjacobianPsi",
      "title": "Jacobian for the psi of a given dimension",
      "topics": [
        "NBjacobianPsi"
      ]
    },
    {
      "page": "NBjacobianRow",
      "title": "A jacobian function of the NB for the row scores",
      "topics": [
        "NBjacobianRow"
      ]
    },
    {
      "page": "NBpsiInfl",
      "title": "The influence function for the psis",
      "topics": [
        "NBpsiInfl"
      ]
    },
    {
      "page": "NBrowInfl",
      "title": "The influence function for the row scores",
      "topics": [
        "NBrowInfl"
      ]
    },
    {
      "page": "permanova",
      "title": "Perform a PERMANOVA analysis for group differences of a predefined cofactor using the pseudo F-statistic",
      "topics": [
        "permanova"
      ]
    },
    {
      "page": "plot.RCM",
      "title": "Plot RC(M) ordination result with the help of ggplot2",
      "topics": [
        "plot.RCM"
      ]
    },
    {
      "page": "plotRespFun",
      "title": "Plot the non-parametric response functions",
      "topics": [
        "plotRespFun"
      ]
    },
    {
      "page": "RCM",
      "title": "Wrapper function for the RCM() function",
      "topics": [
        "RCM",
        "RCM,matrix-method",
        "RCM,phyloseq-method"
      ]
    },
    {
      "page": "RCM_NB",
      "title": "Fit the RC(M) model with the negative binomial distribution.",
      "topics": [
        "RCM_NB"
      ]
    },
    {
      "page": "residualPlot",
      "title": "Make residual plots",
      "topics": [
        "residualPlot"
      ]
    },
    {
      "page": "respFunJacMat",
      "title": "Calculates the Jacobian of the parametric response functions",
      "topics": [
        "respFunJacMat"
      ]
    },
    {
      "page": "respFunScoreMat",
      "title": "Derivative of the Lagrangian of the parametric response function",
      "topics": [
        "respFunScoreMat"
      ]
    },
    {
      "page": "rowMultiply",
      "title": "A function to efficiently row multiply a matrix and a vector",
      "topics": [
        "rowMultiply"
      ]
    },
    {
      "page": "seq_k",
      "title": "A small auxiliary function for the length of the lambdas",
      "topics": [
        "seq_k"
      ]
    },
    {
      "page": "trimOnConfounders",
      "title": "Trim based on confounders to avoid taxa with only zero counts",
      "topics": [
        "trimOnConfounders"
      ]
    },
    {
      "page": "Zeller",
      "title": "Microbiomes of colorectal cancer patients and healthy controls",
      "topics": [
        "Zeller"
      ]
    }
  ],
  "_readme": "https://github.com/bioc/RCM/raw/HEAD/README.md",
  "_rundeps": [
    "ade4",
    "alabama",
    "ape",
    "Biobase",
    "BiocGenerics",
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    "codetools",
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    "lattice",
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    "limma",
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    "magrittr",
    "MASS",
    "Matrix",
    "mgcv",
    "multtest",
    "nleqslv",
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    "numDeriv",
    "permute",
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    "RColorBrewer",
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    "zoo"
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  "_vignettes": [
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      "source": "RCMvignette.Rmd",
      "filename": "RCMvignette.html",
      "title": "Manual for the RCM pacakage",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Publication",
        "Installation",
        "Analysis",
        "Dataset",
        "Unconstrained RCM",
        "Fitting the unconstrained RCM",
        "Adding dimensions",
        "Conditioning",
        "Plotting the uconstrained RCM",
        "Monoplots",
        "Biplots",
        "Adding projections",
        "Assessing the goodness of fit",
        "Testing significance of clusters using PERMANOVA",
        "Constrained RCM",
        "Fitting the constrained RCM model",
        "Plotting the constrained RCM model",
        "Sample-taxon biplot",
        "Variable-taxon biplot",
        "Triplot",
        "Identifying influential observations",
        "Importance of dimensions",
        "Importance parameters \\psi",
        "Log-likelihoods",
        "Inertia",
        "Advanced plotting",
        "Extracting coodinates",
        "Non-squared plots",
        "FAQ",
        "Why are not all my samples shown in the constrained ordination?",
        "Session info"
      ],
      "created": "2017-12-14 16:32:10",
      "modified": "2023-03-29 14:06:49",
      "commits": 32
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