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  "Title": "Imputation for Proteomics",
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  "Description": "Functions to analyse missing value mechanisms and to\nimpute data sets in the context of bottom-up MS-based\nproteomics.",
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    "estim.mix",
    "fast_apply_nb_na",
    "fast_apply_nb_not_na",
    "fast_apply_sd_na_rm_T",
    "fast_apply_sum_na_rm_T",
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    "miss.total.process",
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    "prob.mcar",
    "prob.mcar.tab",
    "sim.data",
    "translatedRandomBeta"
  ],
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    {
      "page": "imp4p-package",
      "title": "Introduction to the IMP4P package",
      "topics": [
        "imp4p-package",
        "imp4p"
      ]
    },
    {
      "page": "estim_bound",
      "title": "Estimation of lower and upper bounds for missing values.",
      "topics": [
        "estim.bound"
      ]
    },
    {
      "page": "estim_mix",
      "title": "Estimation of a mixture model of MCAR and MNAR values in each column of a data matrix.",
      "topics": [
        "estim.mix"
      ]
    },
    {
      "page": "fast_apply_nb_na",
      "title": "Function similar to the function 'apply(X,dim,function(x)sum(is.na(x)))'.",
      "topics": [
        "fast_apply_nb_na"
      ]
    },
    {
      "page": "fast_apply_nb_not_na",
      "title": "Function similar to the function 'apply(X,dim,function(x)sum(!is.na(x)))'.",
      "topics": [
        "fast_apply_nb_not_na"
      ]
    },
    {
      "page": "fast_apply_sd_na_rm_T",
      "title": "Function similar to the function 'apply(X,dim,sd,na.rm=TRUE)'.",
      "topics": [
        "fast_apply_sd_na_rm_T"
      ]
    },
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        "fast_apply_sum_na_rm_T"
      ]
    },
    {
      "page": "fast_sim",
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      ]
    },
    {
      "page": "gen_cond",
      "title": "Function allowing to create a vector indicating the membership of each sample to a condition.",
      "topics": [
        "gen.cond"
      ]
    },
    {
      "page": "impute_igcda",
      "title": "Imputing missing values by assuming that the distribution of complete values is Gaussian in each column of an input matrix. This algorithm is named \"Imputation under a Gaussian Complete Data Assumption\" (IGCDA).",
      "topics": [
        "impute.igcda"
      ]
    },
    {
      "page": "impute_mi",
      "title": "Imputation of data sets containing peptide intensities with a multiple imputation strategy.",
      "topics": [
        "impute.mi"
      ]
    },
    {
      "page": "impute_mix",
      "title": "Imputation using a decision rule under an assumption of a mixture of MCAR and MNAR values.",
      "topics": [
        "impute.mix"
      ]
    },
    {
      "page": "impute_mle",
      "title": "Imputing missing values using a maximum likelihood estimation (MLE).",
      "topics": [
        "impute.mle"
      ]
    },
    {
      "page": "impute_pa",
      "title": "Imputation of peptides having no value in a biological condition (present in a condition / absent in another).",
      "topics": [
        "impute.pa"
      ]
    },
    {
      "page": "impute_PCA",
      "title": "Imputing missing values using Principal Components Analysis.",
      "topics": [
        "impute.PCA"
      ]
    },
    {
      "page": "impute_rand",
      "title": "Imputation of peptides with a random value.",
      "topics": [
        "impute.rand"
      ]
    },
    {
      "page": "impute_RF",
      "title": "Imputing missing values using Random Forest.",
      "topics": [
        "impute.RF"
      ]
    },
    {
      "page": "impute_slsa",
      "title": "Imputing missing values using an adaptation of the LSimpute algorithm (Bo et al. (2004)) to experimental designs. This algorithm is named \"Structured Least Squares Algorithm\" (SLSA).",
      "topics": [
        "impute.slsa"
      ]
    },
    {
      "page": "mi_mix",
      "title": "Multiple imputation from a matrix of probabilities of being MCAR for each missing value.",
      "topics": [
        "mi.mix"
      ]
    },
    {
      "page": "miss_mcar_process",
      "title": "Estimating the MCAR mechanism in a sample.",
      "topics": [
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      ]
    },
    {
      "page": "miss_total_process",
      "title": "Estimating the missing data mechanism in a sample.",
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      ]
    },
    {
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      "title": "Estimating the proportion of MCAR values in biological conditions using the method of Karpievitch (2009).",
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      ]
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      ]
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      ]
    },
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      "title": "Function to generated values following a translated Beta distribution",
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