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Once the scores of interest have been computed and saved in the score tibble, they can be scaled to make them comparable by bounding them between 0 and 1 and harmonise their direction (0 and 1 always mean bad and good performance respectively). This is also a prerequisite for plotting.

Usage

ScaleScores(
  object,
  ref = "Unintegrated",
  rescale = FALSE,
  batch.coeff = 0.4,
  bio.coeff = 0.6
)

Arguments

object

a Seurat object

ref

the name of the integration to use as a reference for scaling. Useful for PCA regression (and density) and cell cycle conservation scores.

rescale

whether to rescale each score between 0 and 1 using min-max normalisation before computing overall scores. This ensures that each metric equally contributes to the overall scores. TRUE by default

batch.coeff

the weight of batch correction performance evaluation scores in the overall score.

bio.coeff

the weight of bio-conservation performance evaluation scores in the overall score.