Bhattacharyya distance between batches in PCA space — pca_bhattacharyya

Computes Bhattacharyya distance between all pairs of batches using fpc:bhattacharyya.matrix after projecting the samples into PCA space with pca.

Usage

pca_bhattacharyya_dist(
  object,
  batch,
  all_features = FALSE,
  center = TRUE,
  scale = "uv",
  nPcs = 3,
  assay.type = NULL,
  ...
)

Arguments

object: a SummarizedExperiment or MetaboSet object
batch: column name of pheno data giving the batch labels
all_features: logical, should all features be used? If FALSE (the default), flagged features are removed before imputation.
center: logical, should the data be centered prior to PCA? (usually yes)
scale: scaling used, as in prep. Default is "uv" for unit variance
nPcs: the number of principal components to use
assay.type: character, assay to be used in case of multiple assays
...: other parameters to pca

Value

A matrix of Bhattacharyya distances between batches.

Examples

data(example_set)
# Batch correction
replicates <- list(which(example_set$QC == "QC"))
batch_corrected <- ruvs_qc(example_set, replicates = replicates)
# Evaluate batch correction
pca_bhattacharyya_dist(example_set, batch = "Batch")
#>          [,1]     [,2]
#> [1,]       NA 11.28682
#> [2,] 11.28682       NA
pca_bhattacharyya_dist(batch_corrected, batch = "Batch")
#> Warning: Variance is below eps for 1 variables. Not scaling them.
#>          [,1]     [,2]
#> [1,]       NA 1.516404
#> [2,] 1.516404       NA