| adjust_p_values | adjust columns |
| aggregate_contrast | Compute fold changes given Contrasts |
| aggregate_intensity_topN | Aggregates top N intensities |
| AnalysisConfiguration | Analysis Configuration |
| AnalysisParameters | Analysis parameters |
| AnalysisTableAnnotation | Create Annotation |
| apply_to_response_matrix | Apply function requiring a matrix to tidy table |
| Benchmark | Benchmark R6 class |
| build_model | Build protein models from data |
| build_models | build dataframe with models for testing |
| complete_cases | Complete cases |
| concrete_AnalysisConfiguration | Cenerate instances of AnalysisTableAnnotation |
| Contrasts | Estimate contrasts using Wald Test |
| contrasts_fisher_exact | Fishers exact test on a datframe |
| ContrastsInterface | Base class for all Contrasts classes |
| contrasts_linfct | compute group averages |
| ContrastsMissing | Compute contrasts with group mean imputation |
| ContrastsModerated | Limma moderated contrasts |
| ContrastsPlotter | plot contrasts |
| ContrastsProDA | ContrastsProDA Wrapper to results produced by proDA |
| ContrastsROPECA | ROPECA reproducibility-optimization method |
| ContrastsTable | holds results when contrasts are added. |
| cor_jackknife_matrix | Compute correlation matrix with jackknife resampling |
| cor_order | Compute correlation matrix |
| data_basicModel_p1807 | Model for debugging |
| data_benchmarkExample | Benchmark data Example |
| data_checksummarizationrobust87 | example data for check |
| data_checksummarizerobust | example data for check |
| data_checksummarizerobust69 | example data for check |
| data_correlatedPeptideList | example data for check |
| data_interactionModel_p1807 | example data for check |
| data_ionstar | example data for check |
| data_IonstarProtein_subsetNorm | example data for check |
| data_multigroupFC | example data for check |
| data_SAINTe_output | SAINT express output |
| data_skylinePRMSample_A | example data for check |
| data_skylineSRM_HL_A | example data for check |
| data_spectronautDIA250_A | example data for check |
| data_test_confusion_matrix_scores | example data for check of scores produced based on confusion... |
| data_Yeast2Factor | example of 2 Factor data |
| dot-get_robscales | compute median and mad on matrix |
| dot-missigness_impute_interactions | Compute interaction averages and impute data using mean of... |
| dot-summarise_missing_contrasts | summarise_missing_contrasts |
| estimate_intensity | Aggregates e.g. protein abundances from peptide abundances |
| filter_byQValue | Filter data by individual and experiment wide thresholds |
| filter_difference | get the difference of two dataset where one is a subset of... |
| filter_proteins_by_peptide_count | Keep only those proteins with 2 IDENTIFIED peptides |
| find_package_file | find file stored in package |
| get_anova_df | anova returning dataframe |
| get_complete_model_fit | retrieve complete model. |
| get_contrast | Compute fold changes given Contrasts |
| get_imputed_contrasts | compute contrasts based on peptide fold changes |
| get_p_values_pbeta | p-value of protein from p.value of the median fold change... |
| get_robscales | compute median and standard deviation for each sample |
| get_UniprotID_from_fasta_header | Extracts uniprot ID |
| hierarchy_counts | Count distinct elements for each level of hierarchy and... |
| hierarchy_counts_sample | Count distinct elements for each level of hierarchy per... |
| intensity_summary_by_hkeys | Summarizes the intensities within hierarchy |
| interaction_missing_stats | compute missingness statistics per hierarchy and factor level |
| INTERNAL_FUNCTIONS_BY_FAMILY | Internal Functions by category |
| ionstar_bench_preprocess | prepare benchmark data |
| isSingular_lm | check if lm model is singular |
| jackknife | Compute jackknive resampling on matrix |
| jackknife_matrix | Compute correlation matrix with jack |
| LFQData | LFQData R6 class |
| LFQDataAggregator | Decorates LFQData with methods to aggregate protein... |
| LFQDataPlotter | LFQDataPlotter – Create various visualization of the LFQdata |
| LFQDataStats | Decorates LFQData with methods to compute statistics of... |
| LFQDataSummariser | Summarize LFQData |
| LFQDataToSummarizedExperiment | converts LFQData object to SummarizedExperiment |
| LFQDataTransformer | Decorate LFQData with Methods for transforming Intensities |
| LFQDataWriter | Write LFQData, or provide outputs for writing. |
| lfq_power_t_test_proteins | Compute theoretical sample sizes from factor level standard... |
| lfq_power_t_test_quantiles | Compute theoretical sample sizes from factor level standard... |
| lfq_power_t_test_quantiles_V2 | estimate sample sizes |
| lfq_write_table | Facade to writing data frame into various file formats. |
| linfct_all_possible_contrasts | create all possible contrasts |
| linfct_factors_contrasts | create contrasts between factor levels |
| linfct_from_model | get linfct from model |
| linfct_matrix_contrasts | linfct_matrix_contrasts |
| LR_test | Likelihood ratio test |
| make_benchmark | make Benchmark |
| make_interaction_column | create interaction column from factors |
| make_model | make interaction model for examples |
| make_reduced_hierarchy_config | Make reduced hierarchy configuration |
| matrix_to_tibble | matrix or data.frame to tibble (taken from tidyquant) |
| medpolish_estimate | Median polish estimate of e.g. protein from peptide... |
| medpolish_estimate_df | Median polish estimates of e.g. protein abundances for entire... |
| medpolish_estimate_dfconfig | Median polish estimates of e.g. protein abundances for entire... |
| medpolish_protein_estimates | median polish from normalized peptide intensities |
| merge_contrasts_results | Merge contrast results coming from two different model. |
| missigness_histogram | Histogram summarizing missigness |
| missigness_impute_factors_interactions | compute per group averages and impute values should... |
| MissingHelpers | compute group mean by LOD |
| missingness_per_condition | Summarize missing in condtion as barplot |
| missingness_per_condition_cumsum | cumulative sums of missing |
| Model | R6 class representing modelling result |
| model_analyse | analyses lmer4 and lm models created using help function... |
| ModelInterface | R6 interface class representing modelling result |
| model_summary | Summarize modelling and error reporting |
| moderated_p_limma | Moderate p-values - limma approach |
| moderated_p_limma_long | Moderate p-value for long table |
| ms_bench_add_scores | adds FDR, TPR and FDP to data. |
| ms_bench_auc | computes auc and pauc using trapez rule |
| multigroup_volcano | plot volcano given multiple contrasts |
| my_contest | applies contrast computation using lmerTest::contest function |
| my_contrast | compute contrasts for full models |
| my_contrast_V1 | handles incomplete models by setting coefficients to 0 |
| my_contrast_V2 | handles incomplete models |
| my_glht | apply multcomp::glht method to linfct |
| names_to_matrix | splits names and creates a matrix |
| normalize_log2_robscale | normalize data by log2 and robust scaling |
| nr_B_in_A | Compute nr of B per A |
| nr_B_in_A_per_sample | how many peptides per protein in each sample |
| nr_obs_experiment | Aggregates e.g. protein abundances from peptide abundances |
| nr_obs_sample | Aggregates e.g. protein abundances from peptide abundances |
| old2new | Convert old proflqua configurations (prolfqua 0.4) to new... |
| PACKAGE_DATA | Package Data |
| pairs_smooth | smoothScatter pairs |
| pairs_w_abline | normal pairs plot with different pch and plus abline |
| panel_cor | correlation panel for pairs plot function (used as default in... |
| panel_hist | histogram panel for pairs function (used as default in... |
| pivot_model_contrasts_2_Wide | pivot model contrasts matrix to wide format produced by... |
| plot_estimate | Plot feature data and result of aggregation |
| plot_heatmap | plot heatmap with annotations |
| plot_heatmap_cor | plot correlation heatmap with annotations |
| plot_hierarchies_add_quantline | Add protein estimate to plot of peptide intensities |
| plot_hierarchies_boxplot | plot peptides by factors and it's levels. |
| plot_hierarchies_boxplot_df | generates peptide level plots for all Proteins |
| plot_hierarchies_line | Plot peptide intensities of protein as a function of the... |
| plot_hierarchies_line_df | Generates peptide level plots for all proteins |
| plot_intensity_distribution_violin | visualize intensity distributions |
| plot_lmer_model_and_data | Make model plot with title - protein Name. |
| plot_lmer_peptide_noRandom | plot peptide intensities per interaction with random effects... |
| plot_lmer_peptide_predictions | Plot prdictions |
| plot_lmer_predicted_interactions | Add predicted values for each interaction |
| plot_NA_heatmap | plot heatmap of NA values |
| plot_pca | plot PCA |
| plot_raster | plot heatmap without any clustering (use to show NA's) |
| plot_sample_correlation | visualize correlation among samples |
| plot_screeplot | plot screeplot |
| plot_stat_density | plot density distribution or ecdf of sd, mean or CV |
| plot_stat_density_median | plot density distribution or ecdf of sd, mean or cv given... |
| plot_stat_violin | plot Violin plot of sd CV or mean |
| plot_stat_violin_median | plot Violin plot of sd CV or mean given intensity lower or... |
| plot_stdv_vs_mean | plot stddev vs mean to asses stability of variance |
| pooled_var | compute pooled variance |
| ProjectStructure | keep track of folder paths and create them if needed |
| prolfqua_data | load data from prolfqua |
| ProteinAnnotation | Decorates LFQData with a row annotation and some protein... |
| R6_extract_values | Extract all value slots in an R6 object |
| rank_by_NA | Ranks peptides/precursors of a protein by NAs (adds new... |
| rank_peptide_by_intensity | ranks precursor - peptide by intensity. |
| remove_large_QValues | Remove rows when qVal_individual_threshold is exceeded |
| remove_NA_rows | Removes rows with more than thresh NA's from matrix |
| remove_small_intensities | Remove rows when intensity lower then threshold |
| render_MQSummary_rmd | render MQ Summary. |
| response_as_matrix | Extract response column of a protein into matrix |
| response_matrix_as_tibble | Takes matrix of responses and converts into tibble |
| rlm_estimate | Estimate e.g. protein abundance from peptides using MASS:rlm |
| rlm_estimate_dfconfig | Estimate protein abundance from peptide abundances using... |
| robust_scale | robust scale wrapper |
| sample_subset | Sample subset of proteins/peptides/precursors |
| scale_with_subset | Scale data using a subset of the data |
| scale_with_subset_by_factors | Scale using a subset of the data, within factor levels (e.g.... |
| scriptCopyHelperVec | copy script files and other from a package to workdir |
| separate_factors | Separates factor columns into starting columns |
| separate_hierarchy | Separates hierarchy columns into starting columns |
| setup_analysis | Setup a tidy table compatible with a 'AnalysisConfiguration' |
| sim_lfq_data | simulate protein level data with two groups |
| sim_lfq_data_2Factor_config | Simulate data, protein, with config with 2 factros Treatment... |
| sim_lfq_data_peptide_config | Simulate data, protein and peptide, with config |
| sim_lfq_data_protein_config | Simulate data, protein, with config |
| spread_response_by_IsotopeLabel | Spreads isotope label heavy and light into two columns |
| squeezeVarRob | Robustly Squeeze Sample Variances |
| strategy | Create custom lmer model |
| summarise_QValues | Compute QValue summaries for each precursor or peptide or... |
| summarize_hierarchy | Summarize hierarchy counts |
| summarize_stats | Compute mean, sd, and CV for all Peptides, or proteins, for... |
| summarize_stats_factors | compute var sd etc for all factor levels |
| summary_ROPECA_median_p.scaled | compute protein level fold changes and p.values (using beta... |
| table_facade | table facade to easily switch implementations |
| table_factors | Table of distinct factors (sample annotation) |
| tidy_to_wide | Transform tidy table into a table with a column of responses... |
| tidy_to_wide_config | transform long to wide |
| transform_work_intensity | Transform intensity |
| UpSet_interaction_missing_stats | UpSetR plot from interaction_missing_stats |
| UpSet_missing_stats | prepare dataframe for UpSetR plot for all samples |
| volcano_Plotly | volcano plotly |
| which_missing | add missing values to x vector based on the values of x |
