Package: BERT 1.3.3

Yannis Schumann

BERT: High Performance Data Integration for Large-Scale Analyses of Incomplete Omic Profiles Using Batch-Effect Reduction Trees (BERT)

Provides efficient batch-effect adjustment of data with missing values. BERT orders all batch effect correction to a tree of pairwise computations. BERT allows parallelization over sub-trees.

Authors:Yannis Schumann [aut, cre], Simon Schlumbohm [aut]

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BERT.pdf |BERT.html
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NEWS

# Install 'BERT' in R:
install.packages('BERT', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/hsu-hpc/bert/issues

On BioConductor:BERT-1.3.0(bioc 3.21)BERT-1.2.0(bioc 3.20)

batcheffectpreprocessingexperimentaldesignqualitycontrol

5.23 score 2 stars 17 scripts 110 downloads 6 exports 92 dependencies

Last updated 2 days agofrom:10fd252685. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-winWARNINGNov 21 2024
R-4.5-linuxWARNINGNov 21 2024
R-4.4-winWARNINGNov 21 2024
R-4.4-macWARNINGNov 21 2024
R-4.3-winWARNINGNov 21 2024
R-4.3-macWARNINGNov 21 2024

Exports:BERTcompute_aswcount_existinggenerate_data_covariablesgenerate_datasetgenerate_truncated_dataset

Dependencies:abindannotateAnnotationDbiaskpassBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobcachemcliclustercodetoolscomprehenrcpp11crayoncurlDBIDelayedArraydplyredgeRfansifastmapforeachformatRfutile.loggerfutile.optionsgenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesgluehmshttrinvgammaIRangesiteratorsjanitorjsonliteKEGGRESTlambda.rlatticelifecyclelimmalocfitlogginglubridatemagrittrMatrixMatrixGenericsmatrixStatsmemoisemgcvmimenlmeopensslpillarpkgconfigplogrpngpurrrR6rlangRSQLiteS4ArraysS4VectorssnakecasesnowSparseArraystatmodstringistringrSummarizedExperimentsurvivalsvasystibbletidyrtidyselecttimechangeUCSC.utilsutf8vctrswithrXMLxtableXVectorzlibbioc

BERT-Vignette

Rendered fromBERT-Vignette.Rmdusingknitr::rmarkdownon Nov 21 2024.

Last update: 2023-11-28
Started: 2023-05-30

Readme and manuals

Help Manual

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