Function reference • prolfqua

All functions
`AnalysisConfiguration`	Analysis Configuration
`AnalysisParameters`	Analysis parameters
`AnalysisTableAnnotation`	Create Annotation
`Benchmark`	Benchmark R6 class
`Contrasts`	Estimate contrasts using Wald Test
`ContrastsInterface`	Base class for all Contrasts classes
`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.
`INTERNAL_FUNCTIONS_BY_FAMILY`	Internal Functions by category
`LFQData`	LFQData R6 class
`LFQDataAggregator`	Decorates LFQData with methods to aggregate protein intensities aggregates intensities
`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
`LFQDataWriter`	Write LFQData, or provide outputs for writing.
`LR_test()`	Likelihood ratio test
`MissingHelpers`	compute group mean by LOD
`Model`	R6 class representing modelling result
`ModelInterface`	R6 interface class representing modelling result
`PACKAGE_DATA`	Package Data
`build_model()`	Build protein models from data
`create_config_Skyline()` `create_config_Spectronaut_Peptide()` `create_config_MQ_peptide()` `create_config_MSFragger_MSstats()`	Cenerate instances of AnalysisTableAnnotation
`ionstar_bench_preprocess()`	prepare benchmark data
`make_benchmark()`	make Benchmark
`merge_contrasts_results()`	Merge contrast results coming from two different model.
`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 Analysis configurations prolfqua 0.5
`prolfqua_data()`	load data from prolfqua
`sim_lfq_data()`	simulate protein level data with two groups
`sim_lfq_data_2Factor_config()`	Simulate data, protein, with config with 2 factros 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
`squeezeVarRob()`	Robustly Squeeze Sample Variances
`strategy_lmer()` `strategy_lm()` `strategy_rlm()` `strategy_glm()`	Create custom lmer model
`summarize_stats_factors()`	compute var sd etc for all factor levels
`which_missing()`	add missing values to x vector based on the values of x

Reference

All functions