Remove batch effects from continuous expression data with limma

This convenience method is intended for visualization or exploratory analysis. Statistical models should usually include batch in their design.

Usage

adjust_batch(
  x,
  experiment,
  batch,
  assay,
  preserve = ~1,
  batch2 = NULL,
  covariates = NULL,
  ...
)

x: A MultiAssayExperiment object.
experiment: Optional experiment name.
batch: Metadata column name or batch vector.
assay: Assay name or one-based assay index.
preserve: Formula describing biological effects to preserve.
batch2: Optional second batch column or vector.
covariates: Optional numeric matrix, or metadata column names, for continuous nuisance covariates.
...: Additional arguments passed to limma::removeBatchEffect().

A corrected feature-by-sample matrix.