Tools for Diagnostics and Corrections of Batch Effects in Proteomics

---

Documentation for package ‘proBatch’ version 1.10.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

adjust_batch_trend_df	Batch correction of normalized data
adjust_batch_trend_dm	Batch correction of normalized data
calculate_feature_CV	Calculate CV distribution for each feature
calculate_peptide_corr_distr	Calculate peptide correlation between and within peptides of one protein
calculate_PVCA	Calculate variance distribution by variable
calculate_sample_corr_distr	Calculates correlation for all pairs of the samples in data matrix, labels as replicated/same_batch/unrelated in output columns (see "Value").
center_feature_batch_means_df	Batch correction of normalized data
center_feature_batch_means_dm	Batch correction of normalized data
center_feature_batch_medians_df	Batch correction of normalized data
center_feature_batch_medians_dm	Batch correction of normalized data
check_sample_consistency	Check if sample annotation is consistent with data matrix and join the two
correct_batch_effects	Batch correction of normalized data
correct_batch_effects_df	Batch correction of normalized data
correct_batch_effects_dm	Batch correction of normalized data
correct_with_ComBat_df	Batch correction of normalized data
correct_with_ComBat_dm	Batch correction of normalized data
create_peptide_annotation	Prepare peptide annotation from long format data frame Create light-weight peptide annotation data frame for selection of illustrative proteins
dates_to_posix	Convert data/time to POSIXct
date_to_sample_order	Convert date/time to POSIXct and rank samples by it
define_sample_order	Defining sample order internally
example_peptide_annotation	Peptide annotation data
example_proteome	Example protein data in long format
example_proteome_matrix	Example protein data in matrix
example_sample_annotation	Sample annotation data version 1
feature_level_diagnostics	Ploting peptide measurements
fit_nonlinear	Fit a non-linear trend (currently optimized for LOESS)
log_transform_df	Functions to log transform raw data before normalization and batch correction
log_transform_dm	Functions to log transform raw data before normalization and batch correction
long_to_matrix	Long to wide data format conversion
matrix_to_long	Wide to long conversion
normalize	Data normalization methods
normalize_data_df	Data normalization methods
normalize_data_dm	Data normalization methods
normalize_sample_medians_df	Data normalization methods
normalize_sample_medians_dm	Data normalization methods
plot_boxplot	Plot per-sample mean or boxplots for initial assessment
plot_corr_matrix	Visualise correlation matrix
plot_CV_distr	Plot CV distribution to compare various steps of the analysis
plot_CV_distr.df	Plot the distribution (boxplots) of per-batch per-step CV of features
plot_heatmap_diagnostic	Plot the heatmap of samples (cols) vs features (rows)
plot_heatmap_generic	Plot the heatmap
plot_hierarchical_clustering	cluster the data matrix to visually inspect which confounder dominates
plot_iRT	Ploting peptide measurements
plot_PCA	plot PCA plot
plot_peptides_of_one_protein	Ploting peptide measurements
plot_peptide_corr_distribution	Create violin plot of peptide correlation distribution
plot_peptide_corr_distribution.corrDF	Create violin plot of peptide correlation distribution
plot_protein_corrplot	Peptide correlation matrix (heatmap)
plot_PVCA	Plot variance distribution by variable
plot_PVCA.df	plot PVCA, when the analysis is completed
plot_sample_corr_distribution	Create violin plot of sample correlation distribution
plot_sample_corr_distribution.corrDF	Create violin plot of sample correlation distribution
plot_sample_corr_heatmap	Sample correlation matrix (heatmap)
plot_sample_mean	Plot per-sample mean or boxplots for initial assessment
plot_sample_mean_or_boxplot	Plot per-sample mean or boxplots for initial assessment
plot_single_feature	Ploting peptide measurements
plot_spike_in	Ploting peptide measurements
plot_split_violin_with_boxplot	Plot split violin plot (convenient to compare distribution before and after)
plot_with_fitting_curve	Ploting peptide measurements
prepare_PVCA_df	prepare the weights of Principal Variance Components
proBatch	proBatch: A package for diagnostics and correction of batch effects, primarily in proteomics
quantile_normalize_df	Data normalization methods
quantile_normalize_dm	Data normalization methods
sample_annotation_to_colors	Generate colors for sample annotation
transform_raw_data	Functions to log transform raw data before normalization and batch correction
unlog_df	Functions to log transform raw data before normalization and batch correction
unlog_dm	Functions to log transform raw data before normalization and batch correction