A B C D F G H I L M N P R S T U V W
| adjust_p_values | adjust columns |
| AggregateLimpa | AggregateLimpa |
| AggregateMedpolish | AggregateMedpolish |
| AggregateRlm | AggregateRlm |
| AggregateTopN | AggregateTopN |
| AnalysisConfiguration | Analysis Configuration |
| annotation_add_contrasts | DRY function: process and export annotated contrasts |
| AnovaExtractor | R6 class for extracting ANOVA results as a data frame |
| build_contrast_analysis | Build a contrast analysis using one of several statistical methods |
| build_model | Build protein models from data |
| build_model_glm_peptide | Build Firth logistic model for nested LFQData |
| build_model_glm_protein | Build Firth logistic model for aggregated LFQData |
| build_model_impute | Build protein models with LOD imputation for failed fits |
| build_model_limma | Build limma model from LFQData |
| build_model_limma_impute | Build limma model with LOD imputation for failed proteins |
| build_model_limma_voom | Build limma model with vooma precision weights (proteomics) |
| build_model_limma_voom_impute | Build limma-voom model with LOD imputation for failed proteins |
| build_model_limpa | Build limpa vooma model from aggregated LFQData |
| center_to_reference_cfg | center to reference |
| ContrastConfiguration | Contrast Configuration |
| Contrasts | Estimate contrasts using Wald Test |
| ContrastsBinomialNestedFacade | Quasibinomial detection-count facade for nested input |
| ContrastsDEqMSFacade | DEqMS contrast analysis facade |
| ContrastsDEqMSVoomFacade | DEqMS contrast analysis with vooma weights facade |
| ContrastsFirth | Estimate contrasts using Wald Test |
| ContrastsFirthFacade | Firth logistic missingness contrast analysis facade |
| ContrastsFirthNestedFacade | Firth logistic missingness contrast analysis facade for nested input |
| ContrastsInterface | Base class for all Contrasts classes |
| ContrastsLimma | Limma-based contrasts (direct limma pipeline) |
| ContrastsLimmaFacade | Limma contrast analysis facade |
| ContrastsLimmaImputeFacade | Limma contrast analysis with LOD imputation facade |
| ContrastsLimmaVoomFacade | Limma-voom contrast analysis facade |
| ContrastsLimmaVoomImputeFacade | Limma-voom contrast analysis with LOD imputation facade |
| ContrastsLimpaFacade | Limpa contrast analysis facade |
| ContrastsLimpaNestedFacade | Limpa contrast analysis facade for nested input |
| ContrastsLmerNestedFacade | Lmer (mixed-model) contrast analysis facade for nested input |
| ContrastsLMFacade | LM contrast analysis facade |
| ContrastsLMImputeFacade | LM contrast analysis with LOD imputation facade |
| ContrastsModerated | Limma moderated contrasts |
| ContrastsModeratedDEqMS | DEqMS count-dependent moderated contrasts |
| ContrastsPlotter | plot contrasts |
| ContrastsRfitFacade | Rfit rank-based regression contrast analysis facade |
| ContrastsRfitImputeFacade | Rfit rank-regression contrast analysis with LOD imputation facade |
| ContrastsRLMFacade | RLM contrast analysis facade |
| ContrastsROPECA | ROPECA reproducibility-optimization method |
| ContrastsROPECANestedFacade | ROPECA contrast analysis facade for nested input |
| ContrastsTable | holds results when contrasts are added. |
| df.residual.rfit_prolfqua | Residual degrees of freedom for an augmented rfit fit |
| FACADE_REGISTRY | Registry of available contrast facade classes |
| find_package_file | find file stored in package |
| generate_contrasts | Combined generate_contrasts |
| generate_contrasts_for_factor | Single-factor contrasts (pairwise comparisons) |
| get_uniprot_id_from_fasta_header | Extracts uniprot ID |
| group_label | group label function |
| HierarchyCountsSample | Count distinct elements for each level of hierarchy per sample |
| impute_from_model | Fill missing responses with predictions from per-subject linear models |
| interaction_contrasts | Interaction contrasts (difference of differences) |
| INTERNAL_FUNCTIONS_BY_FAMILY | Internal Functions by category |
| is_contaminant | Detect contaminant identifiers |
| is_decoy | Detect decoy / reverse-database identifiers |
| level_specific_contrasts | Level-specific contrasts (per secondary level) |
| LFQData | LFQData R6 class |
| LFQDataPlotter | LFQDataPlotter - Create various visualization of the LFQdata |
| LFQDataStats | Decorates LFQData with methods to compute statistics of interactions |
| LFQDataSummariser | Summarize LFQData |
| LFQDataToSummarizedExperiment | converts LFQData object to SummarizedExperiment |
| LFQDataTransformer | Decorate LFQData with Methods for transforming Intensities |
| list_facades | List currently registered contrast facades |
| list_to_AnalysisConfiguration | read minimal yaml to reconstruct configuration |
| list_to_ContrastConfiguration | Rebuild a ContrastConfiguration from a list |
| lookup_facade | Look up a contrast facade by short name |
| LR_test | Likelihood ratio test |
| main_effect_contrasts | main effects contrasts |
| matrix_to_tibble | matrix or data.frame to tibble (taken from tidyquant) |
| merge_contrasts_results | Merge contrast results coming from two different model. |
| MissingHelpers | Group statistics and limit of detection |
| Model | R6 class representing modelling result |
| ModelFirth | R6 class representing modelling result |
| ModelInterface | R6 interface class representing modelling result |
| ModelLimma | R6 class representing a limma modelling result |
| nr_children_experiment | Max nr_children across samples per hierarchy unit |
| nr_features_experiment | Count distinct child features per hierarchy unit |
| nr_obs_sample | Aggregates e.g. protein abundances from peptide abundances |
| PACKAGE_DATA | Package Data |
| pivot_model_contrasts_to_wide | pivot model contrasts matrix to wide format produced by 'contrasts_linfct' and ... |
| prolfqua_data | load data from prolfqua |
| R6_extract_values | Extract all value slots in an R6 object |
| register_facade | Register a contrast facade class |
| setup_analysis | Setup a tidy table compatible with a 'AnalysisConfiguration' |
| sigma.rfit_prolfqua | Scale estimate for an augmented rfit fit |
| sim_lfq_data | simulate protein level data with two groups |
| sim_lfq_data_2factor_config | Simulate data, protein, with config with 2 factors Treatment and Background |
| sim_lfq_data_peptide_config | Simulate data, protein and peptide, with config |
| sim_lfq_data_protein_config | Simulate data, protein, with config |
| StrategyBinomial | Quasibinomial detection-count strategy |
| StrategyLimma | R6 class for limma modelling strategy |
| StrategyLimpa | R6 class for limpa modelling strategy |
| StrategyLM | Linear model strategy (R6 class) |
| StrategyLmer | Linear mixed-effects model strategy (R6 class) |
| StrategyLogistf | Firth's logistic regression strategy (R6 class) |
| StrategyRfit | Rank-based regression strategy (R6 class) |
| StrategyRLM | Robust linear model strategy (R6 class) |
| strategy_binomial | Create a quasibinomial detection-count strategy |
| strategy_limma | Create limma modelling strategy |
| strategy_limpa | Create limpa modelling strategy |
| strategy_lm | Create Firth's logistic regression strategy |
| strategy_lmer | Create Firth's logistic regression strategy |
| strategy_logistf | Create Firth's logistic regression strategy |
| strategy_rfit | Create Firth's logistic regression strategy |
| strategy_rlm | Create Firth's logistic regression strategy |
| summarize_stats_factors | compute var sd etc for all factor levels |
| table_facade | table facade to easily switch implementations |
| upset_interaction_missing_stats | UpSetR plot from interaction_missing_stats |
| vcov.rfit_prolfqua | Named variance-covariance matrix for an augmented rfit fit |
| volcano_plotly | volcano plotly |
| which_missing | add missing values to x vector based on the values of x |