Proteomics Label Free Quantification


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Documentation for package ‘prolfqua’ version 0.99.2

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A B C D F G H I L M N P R S T U V W

-- A --

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

-- B --

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

-- C --

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.

-- D --

df.residual.rfit_prolfqua Residual degrees of freedom for an augmented rfit fit

-- F --

FACADE_REGISTRY Registry of available contrast facade classes
find_package_file find file stored in package

-- G --

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

-- H --

HierarchyCountsSample Count distinct elements for each level of hierarchy per sample

-- I --

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

-- L --

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

-- M --

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

-- N --

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

-- P --

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

-- R --

R6_extract_values Extract all value slots in an R6 object
register_facade Register a contrast facade class

-- S --

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

-- T --

table_facade table facade to easily switch implementations

-- U --

upset_interaction_missing_stats UpSetR plot from interaction_missing_stats

-- V --

vcov.rfit_prolfqua Named variance-covariance matrix for an augmented rfit fit
volcano_plotly volcano plotly

-- W --

which_missing add missing values to x vector based on the values of x