adjust_p_values | adjust columns |
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 |
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_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_ionstar | example data for check |
data_IonstarProtein_subsetNorm | 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... |
dot-get_robscales | compute median and mad on matrix |
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 models. |
get_contrast | Compute fold changes given Contrasts |
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_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 |
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_peptide_predictions | Plot prdictions |
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 |
prolfqua_data | load data from prolfqua |
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_build_models_lm | build dataframe with models for testing |
sim_build_models_lmer | build lmer model from simulated data |
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 |
sim_make_model_lm | make interaction model for examples |
sim_make_model_lmer | make interaction model for examples |
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) |
table_factors_size | 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 |
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