# Differential Abundance Analysis for Phosphoproteomics Data

## Documentation for package ‘pepdiff’ version 1.0.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

assess_missing | calculate the proportion of peptides with missing values per group in a data set.
classify_bf_evidence | Classify Bayes factor into evidence categories
combine_tech_reps | Combine technical replicates
compare | Compare peptide abundances between conditions
compare.data.frame | Default compare method for legacy data frames
compare.pepdiff_data | Compare peptide abundances between conditions
compare_calls | compare sets of significant peptides called by the used data
compare_many | compare many combinations of treatment and control
estimate_result_clusters | plots a Figure of Merit curve to help estimate the number of clusters in the results
fc_qqplot | plot qqplot of fold changes from a comparison
fold_change_matrix | returns a matrix of fold change values
get_bootstrap_percentile | get p values for contrast using boostrap t test
get_comparison | Get results for a specific comparison
get_kruskal_percentile | get p values for contrast using Kruskal-Wallis test
get_peptide | Get results for a specific peptide
get_rp_percentile | get p values for contrast using Rank Products test
get_sig_rows | works out if a peptide has at least one significant value across the experiment Composes a matrix of the 'metric' significance values with peptides in rows, experiments in columns and works out if each peptide row has a value below the stated cut off
get_wilcoxon_percentile | get p values for contrast using Wilcoxon test
import_data | read data from a file
kmeans_by_selected_cols | Perform kmeans of a dataset using just data in selected columns, then return matrices of all columns
list2mat | converts a results object to a matrix as if for direct use in external heatmap functions
long_results | Convert wide format results table to long format
metrics | reports metrics available for significance values
missing_peptides_plot | plot the representation of peptides in each group.
norm_qqplot | draw qqplots for data
plot.pepdiff_data | Plot method for pepdiff_data
plot.pepdiff_results | Plot method for pepdiff_results
plot_bf_distribution | Bayes factor distribution plot
plot_distributions_simple | Simple distribution plot for pepdiff_data
plot_fc | plot histogram of fold change distribution for a comparison
plot_fc_distribution_new | Fold change distribution for pepdiff_results
plot_fit_diagnostics | Plot GLM fit diagnostics
plot_heatmap | makes heatmap from all experiments, filter on a single metric and sig value
plot_kmeans | K-means cluster the data on the samples
plot_missingness_simple | Simple missingness plot for pepdiff_data
plot_pca | plots a pca on the treatment, seconds, bio-rep
plot_pca_simple | Simple PCA plot for pepdiff_data
plot_pvalue_histogram | P-value histogram for pepdiff_results
plot_quant_distributions | draw density plots for data
plot_result | plot the p-values against fold change for the tests used in 'compare()'
plot_volcano_bf | Volcano plot for Bayes factor results
plot_volcano_new | Volcano plot for pepdiff_results
print.pepdiff_data | Print method for pepdiff_data
print.pepdiff_results | Print method for pepdiff_results
p_value_hist | plot histograms of p-values for each test used
read_pepdiff | Read proteomics data into a pepdiff_data object
significant | Extract significant results
subset.pepdiff_data | Subset a pepdiff_data object
summary.pepdiff_data | Summary method for pepdiff_data
summary.pepdiff_results | Summary method for pepdiff_results
test_bayes_t | Bayes factor t-test for two groups
test_bootstrap_t | Bootstrap t-test for two groups
test_rankprod | Rank products test for two groups
test_wilcoxon | Wilcoxon rank-sum test for two groups
times_measured | calculate number of measurements of each peptide in each treatment and time
times_measured_plot | plot the count of the number of times peptides were measured.
volcano_plot | volcano plot the data