Batch correct normalized counts

Batch correct normalized counts for visualizations or other downstream non-DE analysis applications.

batch_correct_norm_cts(
  x,
  de_method = "edger",
  correction_method = "removeBatchEffect",
  new_assay_name = "batch_corr",
  ...
)

Arguments

x

A BbcSE object
de_method

"edger" or "deseq2"
correction_method

"removeBatchEffect" or "combat"
new_assay_name

Name of the batch-corrected counts stored in new assay in 'norm_cts' slot.
...

passed to batch correction function.

Value

A BbcSE object

See also

removeBatchEffect ComBat

Examples

if (FALSE) {
# Default is limma::removeBatchEffect
bbc_obj_batch <- batch_correct_norm_cts(bbc_obj, batch=colData(bbc_obj)$Rep,
design=model.matrix(~Condition, data=colData(bbc_obj)))

plot_PCA(bbc_obj_batch, assay_name = "batch_corr", adonis=FALSE,
color_by="Time", shape_by="Rep")

# Combat is also supported
bbc_obj_batch <- batch_correct_norm_cts(bbc_obj, new_assay_name="combat",
batch=colData(bbc_obj)$Rep, correction_method = "combat", mod =
model.matrix(~Condition, data=colData(bbc_obj)))

plot_PCA(bbc_obj_batch, assay_name = "combat", adonis=FALSE, color_by="Time",
shape_by="Rep")
}