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  "Description": "The prolfqua package integrates essential steps of the\nmass spectrometry based label free quantification data analysis\nworkflow: quality control, data normalization, protein\naggregation, modeling, hypothesis testing and sample size\nestimation. We use prolfqua to : develop highly customizable,\nvisually appealing, and interactive data analysis reports in\npdf or HTML format; to visualize and model simple experimental\ndesigns with a single explanatory variable and complex\nexperiments with multiple factors; to benchmark data\nacquisition, data preprocessing or data modeling methods. We\ndeveloped and improved the package by applying the \"Eating your\nown dog food\" principle, when analysing dozens of proteomics\ndatasets.",
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        "modelling"
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      "topics": [
        "build_contrast_analysis"
      ]
    },
    {
      "page": "build_model",
      "title": "Build protein models from data",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model"
      ]
    },
    {
      "page": "build_model_glm_peptide",
      "title": "Build Firth logistic model for nested LFQData",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_glm_peptide"
      ]
    },
    {
      "page": "build_model_glm_protein",
      "title": "Build Firth logistic model for aggregated LFQData",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_glm_protein"
      ]
    },
    {
      "page": "build_model_impute",
      "title": "Build protein models with LOD imputation for failed fits",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_impute"
      ]
    },
    {
      "page": "build_model_limma",
      "title": "Build limma model from LFQData",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_limma"
      ]
    },
    {
      "page": "build_model_limma_impute",
      "title": "Build limma model with LOD imputation for failed proteins",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_limma_impute"
      ]
    },
    {
      "page": "build_model_limma_voom",
      "title": "Build limma model with vooma precision weights (proteomics)",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_limma_voom"
      ]
    },
    {
      "page": "build_model_limma_voom_impute",
      "title": "Build limma-voom model with LOD imputation for failed proteins",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_limma_voom_impute"
      ]
    },
    {
      "page": "build_model_limpa",
      "title": "Build limpa vooma model from aggregated LFQData",
      "concept": [
        "modelling"
      ],
      "topics": [
        "build_model_limpa"
      ]
    },
    {
      "page": "center_to_reference_cfg",
      "title": "center to reference",
      "topics": [
        "center_to_reference_cfg"
      ]
    },
    {
      "page": "ContrastConfiguration",
      "title": "Contrast Configuration",
      "concept": [
        "configuration"
      ],
      "topics": [
        "ContrastConfiguration"
      ]
    },
    {
      "page": "Contrasts",
      "title": "Estimate contrasts using Wald Test",
      "concept": [
        "modelling"
      ],
      "topics": [
        "Contrasts"
      ]
    },
    {
      "page": "ContrastsBinomialNestedFacade",
      "title": "Quasibinomial detection-count facade for nested input",
      "topics": [
        "ContrastsBinomialNestedFacade"
      ]
    },
    {
      "page": "ContrastsDEqMSFacade",
      "title": "DEqMS contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsDEqMSFacade"
      ]
    },
    {
      "page": "ContrastsDEqMSVoomFacade",
      "title": "DEqMS contrast analysis with vooma weights facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsDEqMSVoomFacade"
      ]
    },
    {
      "page": "ContrastsFirth",
      "title": "Estimate contrasts using Wald Test",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsFirth"
      ]
    },
    {
      "page": "ContrastsFirthFacade",
      "title": "Firth logistic missingness contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsFirthFacade"
      ]
    },
    {
      "page": "ContrastsFirthNestedFacade",
      "title": "Firth logistic missingness contrast analysis facade for nested input",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsFirthNestedFacade"
      ]
    },
    {
      "page": "ContrastsInterface",
      "title": "Base class for all Contrasts classes",
      "topics": [
        "ContrastsInterface"
      ]
    },
    {
      "page": "ContrastsLimma",
      "title": "Limma-based contrasts (direct limma pipeline)",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLimma"
      ]
    },
    {
      "page": "ContrastsLimmaFacade",
      "title": "Limma contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLimmaFacade"
      ]
    },
    {
      "page": "ContrastsLimmaImputeFacade",
      "title": "Limma contrast analysis with LOD imputation facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLimmaImputeFacade"
      ]
    },
    {
      "page": "ContrastsLimmaVoomFacade",
      "title": "Limma-voom contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLimmaVoomFacade"
      ]
    },
    {
      "page": "ContrastsLimmaVoomImputeFacade",
      "title": "Limma-voom contrast analysis with LOD imputation facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLimmaVoomImputeFacade"
      ]
    },
    {
      "page": "ContrastsLimpaFacade",
      "title": "Limpa contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLimpaFacade"
      ]
    },
    {
      "page": "ContrastsLimpaNestedFacade",
      "title": "Limpa contrast analysis facade for nested input",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLimpaNestedFacade"
      ]
    },
    {
      "page": "ContrastsLmerNestedFacade",
      "title": "Lmer (mixed-model) contrast analysis facade for nested input",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLmerNestedFacade"
      ]
    },
    {
      "page": "ContrastsLMFacade",
      "title": "LM contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLMFacade"
      ]
    },
    {
      "page": "ContrastsLMImputeFacade",
      "title": "LM contrast analysis with LOD imputation facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsLMImputeFacade"
      ]
    },
    {
      "page": "ContrastsModerated",
      "title": "Limma moderated contrasts",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsModerated"
      ]
    },
    {
      "page": "ContrastsModeratedDEqMS",
      "title": "DEqMS count-dependent moderated contrasts",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsModeratedDEqMS"
      ]
    },
    {
      "page": "ContrastsPlotter",
      "title": "plot contrasts",
      "concept": [
        "modelling",
        "plotting"
      ],
      "topics": [
        "ContrastsPlotter"
      ]
    },
    {
      "page": "ContrastsRfitFacade",
      "title": "Rfit rank-based regression contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsRfitFacade"
      ]
    },
    {
      "page": "ContrastsRfitImputeFacade",
      "title": "Rfit rank-regression contrast analysis with LOD imputation facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsRfitImputeFacade"
      ]
    },
    {
      "page": "ContrastsRLMFacade",
      "title": "RLM contrast analysis facade",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsRLMFacade"
      ]
    },
    {
      "page": "ContrastsROPECA",
      "title": "ROPECA reproducibility-optimization method",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsROPECA"
      ]
    },
    {
      "page": "ContrastsROPECANestedFacade",
      "title": "ROPECA contrast analysis facade for nested input",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsROPECANestedFacade"
      ]
    },
    {
      "page": "ContrastsTable",
      "title": "holds results when contrasts are added.",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ContrastsTable"
      ]
    },
    {
      "page": "df.residual.rfit_prolfqua",
      "title": "Residual degrees of freedom for an augmented rfit fit",
      "concept": [
        "modelling"
      ],
      "topics": [
        "df.residual.rfit_prolfqua"
      ]
    },
    {
      "page": "FACADE_REGISTRY",
      "title": "Registry of available contrast facade classes",
      "topics": [
        "FACADE_REGISTRY"
      ]
    },
    {
      "page": "find_package_file",
      "title": "find file stored in package",
      "topics": [
        "find_package_file"
      ]
    },
    {
      "page": "generate_contrasts",
      "title": "Combined generate_contrasts",
      "concept": [
        "contrasts"
      ],
      "topics": [
        "generate_contrasts"
      ]
    },
    {
      "page": "generate_contrasts_for_factor",
      "title": "Single-factor contrasts (pairwise comparisons)",
      "concept": [
        "contrasts"
      ],
      "topics": [
        "generate_contrasts_for_factor"
      ]
    },
    {
      "page": "get_uniprot_id_from_fasta_header",
      "title": "Extracts uniprot ID",
      "concept": [
        "utilities"
      ],
      "topics": [
        "get_uniprot_id_from_fasta_header"
      ]
    },
    {
      "page": "group_label",
      "title": "group label function",
      "concept": [
        "modelling"
      ],
      "topics": [
        "group_label"
      ]
    },
    {
      "page": "HierarchyCountsSample",
      "title": "Count distinct elements for each level of hierarchy per sample",
      "concept": [
        "summary"
      ],
      "topics": [
        "HierarchyCountsSample"
      ]
    },
    {
      "page": "impute_from_model",
      "title": "Fill missing responses with predictions from per-subject linear models",
      "concept": [
        "modelling"
      ],
      "topics": [
        "impute_from_model"
      ]
    },
    {
      "page": "interaction_contrasts",
      "title": "Interaction contrasts (difference of differences)",
      "concept": [
        "contrasts"
      ],
      "topics": [
        "interaction_contrasts"
      ]
    },
    {
      "page": "INTERNAL_FUNCTIONS_BY_FAMILY",
      "title": "Internal Functions by category",
      "concept": [
        "aggregation",
        "configuration",
        "modelling",
        "plotting",
        "preprocessing",
        "stats",
        "summary",
        "utilities"
      ],
      "topics": [
        "INTERNAL_FUNCTIONS_BY_FAMILY"
      ]
    },
    {
      "page": "is_contaminant",
      "title": "Detect contaminant identifiers",
      "concept": [
        "utilities"
      ],
      "topics": [
        "is_contaminant"
      ]
    },
    {
      "page": "is_decoy",
      "title": "Detect decoy / reverse-database identifiers",
      "concept": [
        "utilities"
      ],
      "topics": [
        "is_decoy"
      ]
    },
    {
      "page": "level_specific_contrasts",
      "title": "Level-specific contrasts (per secondary level)",
      "concept": [
        "contrasts"
      ],
      "topics": [
        "level_specific_contrasts"
      ]
    },
    {
      "page": "LFQData",
      "title": "LFQData R6 class",
      "concept": [
        "LFQData"
      ],
      "topics": [
        "LFQData"
      ]
    },
    {
      "page": "LFQDataPlotter",
      "title": "LFQDataPlotter -- Create various visualization of the LFQdata",
      "concept": [
        "LFQData"
      ],
      "topics": [
        "LFQDataPlotter"
      ]
    },
    {
      "page": "LFQDataStats",
      "title": "Decorates LFQData with methods to compute statistics of interactions",
      "concept": [
        "LFQData"
      ],
      "topics": [
        "LFQDataStats"
      ]
    },
    {
      "page": "LFQDataSummariser",
      "title": "Summarize LFQData",
      "concept": [
        "LFQData"
      ],
      "topics": [
        "LFQDataSummariser"
      ]
    },
    {
      "page": "LFQDataToSummarizedExperiment",
      "title": "converts LFQData object to SummarizedExperiment",
      "concept": [
        "LFQData"
      ],
      "topics": [
        "LFQDataToSummarizedExperiment"
      ]
    },
    {
      "page": "LFQDataTransformer",
      "title": "Decorate LFQData with Methods for transforming Intensities",
      "topics": [
        "LFQDataTransformer"
      ]
    },
    {
      "page": "list_facades",
      "title": "List currently registered contrast facades",
      "concept": [
        "modelling"
      ],
      "topics": [
        "list_facades"
      ]
    },
    {
      "page": "list_to_AnalysisConfiguration",
      "title": "read minimal yaml to reconstruct configuration",
      "topics": [
        "list_to_AnalysisConfiguration"
      ]
    },
    {
      "page": "list_to_ContrastConfiguration",
      "title": "Rebuild a ContrastConfiguration from a list",
      "concept": [
        "configuration"
      ],
      "topics": [
        "list_to_ContrastConfiguration"
      ]
    },
    {
      "page": "lookup_facade",
      "title": "Look up a contrast facade by short name",
      "concept": [
        "modelling"
      ],
      "topics": [
        "lookup_facade"
      ]
    },
    {
      "page": "LR_test",
      "title": "Likelihood ratio test",
      "concept": [
        "modelling"
      ],
      "topics": [
        "LR_test"
      ]
    },
    {
      "page": "main_effect_contrasts",
      "title": "main effects contrasts",
      "concept": [
        "contrasts"
      ],
      "topics": [
        "main_effect_contrasts"
      ]
    },
    {
      "page": "matrix_to_tibble",
      "title": "matrix or data.frame to tibble (taken from tidyquant)",
      "concept": [
        "utilities"
      ],
      "topics": [
        "matrix_to_tibble"
      ]
    },
    {
      "page": "merge_contrasts_results",
      "title": "Merge contrast results coming from two different model.",
      "concept": [
        "modelling"
      ],
      "topics": [
        "merge_contrasts_results"
      ]
    },
    {
      "page": "MissingHelpers",
      "title": "Group statistics and limit of detection",
      "topics": [
        "MissingHelpers"
      ]
    },
    {
      "page": "Model",
      "title": "R6 class representing modelling result",
      "concept": [
        "modelling"
      ],
      "topics": [
        "Model"
      ]
    },
    {
      "page": "ModelFirth",
      "title": "R6 class representing modelling result",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ModelFirth"
      ]
    },
    {
      "page": "ModelInterface",
      "title": "R6 interface class representing modelling result",
      "topics": [
        "ModelInterface"
      ]
    },
    {
      "page": "ModelLimma",
      "title": "R6 class representing a limma modelling result",
      "concept": [
        "modelling"
      ],
      "topics": [
        "ModelLimma"
      ]
    },
    {
      "page": "nr_children_experiment",
      "title": "Max nr_children across samples per hierarchy unit",
      "topics": [
        "nr_children_experiment"
      ]
    },
    {
      "page": "nr_features_experiment",
      "title": "Count distinct child features per hierarchy unit",
      "topics": [
        "nr_features_experiment"
      ]
    },
    {
      "page": "nr_obs_sample",
      "title": "Aggregates e.g. protein abundances from peptide abundances",
      "topics": [
        "nr_obs_sample"
      ]
    },
    {
      "page": "PACKAGE_DATA",
      "title": "Package Data",
      "concept": [
        "data"
      ],
      "topics": [
        "PACKAGE_DATA"
      ]
    },
    {
      "page": "pivot_model_contrasts_to_wide",
      "title": "pivot model contrasts matrix to wide format produced by `contrasts_linfct` and ...",
      "concept": [
        "modelling"
      ],
      "topics": [
        "pivot_model_contrasts_to_wide"
      ]
    },
    {
      "page": "prolfqua_data",
      "title": "load data from prolfqua",
      "concept": [
        "data"
      ],
      "topics": [
        "prolfqua_data"
      ]
    },
    {
      "page": "R6_extract_values",
      "title": "Extract all value slots in an R6 object",
      "concept": [
        "configuration"
      ],
      "topics": [
        "R6_extract_values"
      ]
    },
    {
      "page": "register_facade",
      "title": "Register a contrast facade class",
      "concept": [
        "modelling"
      ],
      "topics": [
        "register_facade"
      ]
    },
    {
      "page": "setup_analysis",
      "title": "Setup a tidy table compatible with a 'AnalysisConfiguration'",
      "concept": [
        "configuration"
      ],
      "topics": [
        "setup_analysis"
      ]
    },
    {
      "page": "sigma.rfit_prolfqua",
      "title": "Scale estimate for an augmented rfit fit",
      "concept": [
        "modelling"
      ],
      "topics": [
        "sigma.rfit_prolfqua"
      ]
    },
    {
      "page": "sim_lfq_data",
      "title": "simulate protein level data with two groups",
      "topics": [
        "sim_lfq_data"
      ]
    },
    {
      "page": "sim_lfq_data_2Factor_config",
      "title": "Simulate data, protein, with config with 2 factors Treatment and Background",
      "topics": [
        "sim_lfq_data_2factor_config"
      ]
    },
    {
      "page": "sim_lfq_data_peptide_config",
      "title": "Simulate data, protein and peptide, with config",
      "topics": [
        "sim_lfq_data_peptide_config"
      ]
    },
    {
      "page": "sim_lfq_data_protein_config",
      "title": "Simulate data, protein, with config",
      "topics": [
        "sim_lfq_data_protein_config"
      ]
    },
    {
      "page": "strategy_binomial",
      "title": "Create a quasibinomial detection-count strategy",
      "topics": [
        "strategy_binomial"
      ]
    },
    {
      "page": "strategy_limma",
      "title": "Create limma modelling strategy",
      "concept": [
        "modelling"
      ],
      "topics": [
        "strategy_limma"
      ]
    },
    {
      "page": "strategy_limpa",
      "title": "Create limpa modelling strategy",
      "concept": [
        "modelling"
      ],
      "topics": [
        "strategy_limpa"
      ]
    },
    {
      "page": "strategy",
      "title": "Create Firth's logistic regression strategy",
      "concept": [
        "modelling"
      ],
      "topics": [
        "strategy_lm",
        "strategy_lmer",
        "strategy_logistf",
        "strategy_rfit",
        "strategy_rlm"
      ]
    },
    {
      "page": "StrategyBinomial",
      "title": "Quasibinomial detection-count strategy",
      "topics": [
        "StrategyBinomial"
      ]
    },
    {
      "page": "StrategyLimma",
      "title": "R6 class for limma modelling strategy",
      "concept": [
        "modelling"
      ],
      "topics": [
        "StrategyLimma"
      ]
    },
    {
      "page": "StrategyLimpa",
      "title": "R6 class for limpa modelling strategy",
      "concept": [
        "modelling"
      ],
      "topics": [
        "StrategyLimpa"
      ]
    },
    {
      "page": "StrategyLM",
      "title": "Linear model strategy (R6 class)",
      "concept": [
        "modelling"
      ],
      "topics": [
        "StrategyLM"
      ]
    },
    {
      "page": "StrategyLmer",
      "title": "Linear mixed-effects model strategy (R6 class)",
      "concept": [
        "modelling"
      ],
      "topics": [
        "StrategyLmer"
      ]
    },
    {
      "page": "StrategyLogistf",
      "title": "Firth's logistic regression strategy (R6 class)",
      "concept": [
        "modelling"
      ],
      "topics": [
        "StrategyLogistf"
      ]
    },
    {
      "page": "StrategyRfit",
      "title": "Rank-based regression strategy (R6 class)",
      "concept": [
        "modelling"
      ],
      "topics": [
        "StrategyRfit"
      ]
    },
    {
      "page": "StrategyRLM",
      "title": "Robust linear model strategy (R6 class)",
      "concept": [
        "modelling"
      ],
      "topics": [
        "StrategyRLM"
      ]
    },
    {
      "page": "summarize_stats_factors",
      "title": "compute var sd etc for all factor levels",
      "topics": [
        "summarize_stats_factors"
      ]
    },
    {
      "page": "table_facade",
      "title": "table facade to easily switch implementations",
      "concept": [
        "utilities"
      ],
      "topics": [
        "table_facade"
      ]
    },
    {
      "page": "UpSet_interaction_missing_stats",
      "title": "UpSetR plot from interaction_missing_stats",
      "concept": [
        "imputation",
        "plotting"
      ],
      "topics": [
        "upset_interaction_missing_stats"
      ]
    },
    {
      "page": "vcov.rfit_prolfqua",
      "title": "Named variance-covariance matrix for an augmented rfit fit",
      "concept": [
        "modelling"
      ],
      "topics": [
        "vcov.rfit_prolfqua"
      ]
    },
    {
      "page": "volcano_Plotly",
      "title": "volcano plotly",
      "topics": [
        "volcano_plotly"
      ]
    },
    {
      "page": "which_missing",
      "title": "add missing values to x vector based on the values of x",
      "topics": [
        "which_missing"
      ]
    }
  ],
  "_readme": "https://github.com/BiocStaging/prolfqua/raw/HEAD/README.md",
  "_rundeps": [
    "askpass",
    "backports",
    "base64enc",
    "beeswarm",
    "BiocGenerics",
    "bit",
    "bit64",
    "boot",
    "broom",
    "bslib",
    "cachem",
    "circlize",
    "cli",
    "clipr",
    "clue",
    "cluster",
    "codetools",
    "colorspace",
    "ComplexHeatmap",
    "cpp11",
    "crayon",
    "crosstalk",
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