Hierarchical Batch-Effect Adjustment with Trees

[Up] [Top]

Documentation for package ‘BERT’ version 1.0.0

Help Pages

adjustment_step Adjust a hierarchy level sequentially.
adjust_node Adjust two batches to each other.
BERT Adjust data using the BERT algorithm.
chunk_data Chunks data into n segments with (close-to) equivalent number of batches and stores them in temporary RDS files
compute_asw Compute the average silhouette width (ASW) for the dataset with respect to both label and batch.
count_existing Count the number of numeric features in this dataset. Columns labeled "Batch", "Sample" or "Label" will be ignored.
format_DF Format the data as expected by BERT.
generate_dataset Generate dataset with batch-effects and biological labels using a simple LS model
generate_data_covariables Generate dataset with batch-effects and 2 classes with a specified imbalance.
get_adjustable_features Check, which features contain enough numeric data to be adjusted (at least 2 numeric values)
get_adjustable_features_with_mod Check, which features contain enough numeric data to be adjusted (at least 2 numeric values per batch and covariate level)
identify_adjustableFeatures_refs Identifies the adjustable features using only the references. Similar to the function in adjust_features.R but with different arguments
identify_references Identifies the references to use for this specific batch effect adjustment
ordinal_encode Ordinal encoding of a vector.
parallel_bert Adjusts all chunks of data (in parallel) as far as possible.
removeBatchEffectRefs A method to remove batch effects estimated from a subset (references) per batch only. Source code is heavily based on limma::removeBatchEffects by Gordon Smyth and Carolyn de Graaf
replace_missing Replaces missing values (NaN) by NA, this appears to be faster
strip_Covariable Strip column labelled Cov_1 from dataframe.
validate_bert_input Verifies that the input to BERT is valid.
validate_input_generate_dataset Validate the user input to the function generate_dataset. Raises an error if and only if the input is malformatted.
verify_references Verify that the Reference column of the data contains only zeros and ones (if it is present at all)