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Split a Seurat object into per-batch layers and prepare it for integration.

split_layers_by_batch.Rd

Drops the scaled data, reductions, graphs, and clustering columns, then splits the assay layers by a metadata column — splitting the layers rather than the object is what the Seurat 5 IntegrateLayers() workflow expects.

Usage

split_layers_by_batch(
  x,
  batch_var = "orig.ident",
  assay = "RNA",
  num_variable_genes = 3000,
  num_dim = 50,
  log_file = NULL
)

Arguments

x

Seurat object.

batch_var

Metadata column to split the layers by.

assay

Assay to split.

num_variable_genes

Number of variable features. Matches the single-sample default.

num_dim

Number of principal components to compute.

log_file

Filename for the log file.

Value

A Seurat object with split layers and a "pca" reduction.

Details

Everything after the split runs through the same verbs as the single-sample path (normalize_counts(), run_pca()), so the two workflows cannot drift apart on parameters. integrate_layers() then consumes the resulting "pca" reduction.