regularise_image: regularise image

In patrickCNMartin/Vesalius: Vesalius: Dissecting Tissue Anatomy from Spatial Transcriptomic Data

regularise image

Description

regularise_image denoise Vesalius images via variance regularization

Usage

regularise_image(
  vesalius_assay,
  dimensions = seq(1, 3),
  embedding = "last",
  lambda = 1,
  niter = 100,
  verbose = TRUE
)

Arguments

vesalius_assay	a vesalius_assay object
dimensions	numeric vector of latent space dimensions to use.
embedding	character string describing which embedding should be used.
lambda	numeric - positive real numbers describing regularization parameter (see details)
niter	numeric - number of variance regularization iterations (Default = 100)
verbose	logical - progress message output.

Details

Image regularization can be seen as a form of image denoising. Details on each method can be found in the tvR package under the denoise2 function https://cran.r-project.org/web/packages/tvR/tvR.pdf.

A higher value for lambda will results in a smoother image. It should be noted that in the context of spatial omics the more sparse the points in the data (the more space between coordinates), the more you will need to increase the value of lambda to obtain better denoising.

Value

a vesalius_assay

Examples

## Not run: 
data(vesalius)
# First we build a simple object
ves <- build_vesalius_object(coordinates, counts)
# We can do a simple run
ves <- build_vesalius_embeddings(ves)

# simple regularisation
ves <- regularise_image(ves, embedding = "PCA")

## End(Not run)

patrickCNMartin/Vesalius documentation built on April 17, 2025, 11:31 p.m.