{ "_id": "6a103250acfb0bcc41c9773c", "Package": "emcAdr", "Type": "Package", "Title": "Evolutionary Version of the Metropolis-Hastings Algorithm", "Version": "1.3", "Date": "2026-02-04", "Author": "Jules Bangard [aut, cre] (ORCID:\n)", "Authors@R": "c(\nperson(\"Jules\", \"Bangard\", , \"jules.bangard@etu.unistra.fr\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0007-4670-7860\")))", "Maintainer": "Jules Bangard ", "Description": "Provides computational methods for detecting adverse\nhigh-order drug interactions from individual case safety\nreports using statistical techniques, allowing the exploration\nof higher-order interactions among drug cocktails.", "License": "GPL-3", "RoxygenNote": "7.3.2", "LazyData": "true", "VignetteBuilder": "knitr", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-12 08:36:10 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-02-05 13:41:57 UTC", "RemoteUrl": "https://github.com/cran/emcAdr", 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"trueDistributionSizeTwoCocktail" ], "_datasets": [ { "name": "ATC_Tree_UpperBound_2024", "title": "ATC Tree Upper Bound 2024", "object": "ATC_Tree_UpperBound_2024", "class": [ "data.frame" ], "fields": [ "ATCCode", "Name", "ATC_length", "upperBound" ], "rows": 6809, "table": true, "tojson": true }, { "name": "FAERS_myopathy", "title": "FAERS Myopathy Dataset", "object": "FAERS_myopathy", "class": [ "data.frame" ], "fields": [ "patientATC", "patientADR" ], "rows": 100000, "table": true, "tojson": true } ], "_help": [ { "page": "emcAdr-package", "title": "Evolutionary Version of the Metropolis-Hastings Algorithm", "topics": [ "emcAdr-package", "emcAdr" ] }, { "page": "ATC_Tree_UpperBound_2024", "title": "ATC Tree Upper Bound 2024", "topics": [ "ATC_Tree_UpperBound_2024" ] }, { "page": "ATCtoNumeric", "title": "Convert ATC Code for each patients to the corresponding DFS number of the ATC tree", "topics": [ "ATCtoNumeric" ] }, { "page": "calculate_divergence", "title": "Calculate the divergence between 2 distributions (the true Distribution and the learned one)", "topics": [ "calculate_divergence" ] }, { "page": "clustering_genetic_algorithm", "title": "Clustering of the solutions of the genetic algorithm using the hclust algorithm", "topics": [ "clustering_genetic_algorithm" ] }, { "page": "combination_data_frame", "title": "Generate Matrix for Drug Combinations", "topics": [ "combination_data_frame" ] }, { "page": "compute_hypergeom_cocktail", "title": "Function used to compute the Hypergeometric score on a cocktail", "topics": [ "compute_hypergeom_cocktail" ] }, { "page": "compute_hypergeom_on_list", "title": "Function used to compute the Hypergeometric score on a list of cocktails", "topics": [ "compute_hypergeom_on_list" ] }, { "page": "compute_RR_on_list", "title": "Function used to compute the Relative Risk on a list of cocktails", "topics": [ "compute_RR_on_list" ] }, { "page": "computeMetrics_size2", "title": "Function used in the reference article to compare diverse Disproportionality Analysis metrics", "topics": [ "computeMetrics_size2" ] }, { "page": "csv_to_population", "title": "Function used to convert your genetic algorithm results that are stored into a .csv file to a Data structure that can be used by the clustering algorithm", "topics": [ "csv_to_population" ] }, { "page": "DistributionApproximation", "title": "The MCMC method that runs the random walk on a single cocktail in order to estimate the distribution of score among cocktails of size Smax.", "topics": [ "DistributionApproximation" ] }, { "page": "FAERS_myopathy", "title": "FAERS Myopathy Dataset", "topics": [ "FAERS_myopathy" ] }, { "page": "GeneticAlgorithm", "title": "Genetic algorithm, trying to reach riskiest cocktails (the ones which maximize the fitness function, Hypergeometric score in our case)", "topics": [ "GeneticAlgorithm" ] }, { "page": "get_dissimilarity_from_cocktail_list", "title": "Recover the square matrix of distance between cocktails where the index (i,j) of the matrix is the distance between cocktails i and j in an arbitrary cocktail list", "topics": [ "get_dissimilarity_from_cocktail_list" ] }, { "page": "get_dissimilarity_from_genetic_results", "title": "Recover the square matrix of distance between cocktails where the index (i,j) of the matrix is the distance between cocktails i and j in the genetic_results list.", "topics": [ "get_dissimilarity_from_genetic_results" ] }, { "page": "get_dissimilarity_from_txt_file", "title": "Recover the square matrix of distance between cocktails where the index (i,j) of the matrix is the distance between cocktails i and j in the csv file containing results of genetic algorithm", "topics": [ "get_dissimilarity_from_txt_file" ] }, { "page": "hclust_genetic_solution", "title": "Clustering of the solutions of the genetic algorithm using the hclust algorithm", "topics": [ "hclust_genetic_solution" ] }, { "page": "histogramToDitribution", "title": "Convert the histogram returned by the DistributionApproximation function, to a real number distribution (that can be used in a test for example)", "topics": [ "histogramToDitribution" ] }, { "page": "hyperparam_test_genetic_algorithm", "title": "This function can be used in order to try different set of parameters for the genetic algorithm in a convenient way. This will run each combination of mutation_rate, nb_elite and alphas possible nb_test_desired times. For each sets of parameters, results will be saved in a file named according to the set of parameter. One can regroup the results of each run in a csv file by using the print_csv function specifying the names of each file that needs to be treated and the number of performed runs on each parameter set", "topics": [ "hyperparam_test_genetic_algorithm" ] }, { "page": "int_cocktail_to_string_cocktail", "title": "Function used to convert integer cocktails (like the one outputed by the distributionApproximation function) to string cocktail in order to make them more readable", "topics": [ "int_cocktail_to_string_cocktail" ] }, { "page": "OutsandingScoreToDistribution", "title": "Output the outstanding score (Outstanding_score) outputed by the MCMC algorithm in a special format", "topics": [ "OutsandingScoreToDistribution" ] }, { "page": "p_value_cocktails", "title": "Used to add the p_value to each cocktail of cocktail list", "topics": [ "p_value_cocktails" ] }, { "page": "p_value_csv_file", "title": "Used to add the p_value to each cocktail of a csv_file that is an output of the genetic algorithm", "topics": [ "p_value_csv_file" ] }, { "page": "p_value_genetic_results", "title": "Used to add the p_value to each cocktail of an output of the genetic algorithm", "topics": [ "p_value_genetic_results" ] }, { "page": "p_value_on_sampled", "title": "Calculate p-value of sampled value", "topics": [ "p_value_on_sampled" ] }, { "page": "plot_evolution", "title": "Plot the evolution of the mean and the best value of the population used by the GeneticAlgorithm", "topics": [ "plot_evolution" ] }, { "page": "plot_frequency", "title": "Plot the histogram of the approximation of the RR distribution", "topics": [ "plot_frequency" ] }, { "page": "print_csv", "title": "Print every cocktails found during the genetic algorithm when used with the hyperparam_test_genetic_algorithm function. This enables to condense the solutions found in each files by collapsing similar cocktail in a single row by cocktail.", "topics": [ "print_csv" ] }, { "page": "qq_plot_output", "title": "Make a Quantile-Quantile diagram from the output of the MCMC algorithm (DistributionAproximation) and the algorithm that exhaustively calculates the distribution", "topics": [ "qq_plot_output" ] }, { "page": "remove_higher_cocktails", "title": "Filter out drug cocktails with high-level ATC classifications", "topics": [ "remove_higher_cocktails" ] }, { "page": "run_firth_regression", "title": "Firth Penalized Logistic Regression for Drug Cocktails", "topics": [ "run_firth_regression" ] }, { "page": "string_list_to_int_cocktails", "title": "Function used to convert a string vector of drugs in form \"drug1:drug2\" to a vector of index of the ATC tree ex: c(ATC_index(drug1), ATC_index(drugs2))", "topics": [ "string_list_to_int_cocktails" ] }, { "page": "trueDistributionDrugs", "title": "The true distribution of the score among every single nodes of the ATC", "topics": [ "trueDistributionDrugs" ] }, { "page": "trueDistributionSizeTwoCocktail", "title": "The true distribution of the score among every size-two cocktails", "topics": [ "trueDistributionSizeTwoCocktail" ] } ], "_readme": "https://github.com/cran/emcAdr/raw/HEAD/README.md", "_rundeps": [ "askpass", "backports", "bit", "bit64", "boot", "broom", "cli", "clipr", "codetools", "cpp11", "crayon", "dbscan", "dplyr", "farver", "forcats", "foreach", "formula.tools", "generics", "ggplot2", "glmnet", "glue", "gtable", "haven", "here", "hms", "isoband", "iterators", "jomo", "jsonlite", "labeling", "lattice", "lifecycle", "lme4", "logistf", "magrittr", "MASS", "Matrix", "mgcv", "mice", "minqa", "mitml", "nlme", "nloptr", "nnet", "numDeriv", "openssl", "operator.tools", "ordinal", "pan", "pillar", "pkgconfig", "png", "prettyunits", "progress", "purrr", "R6", "rappdirs", "rbibutils", "RColorBrewer", "Rcpp", "RcppArmadillo", 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