runAutoencoderDenoising: Denoise expression matrix

In theMILOlab/SPATA2: A Toolbox for Spatial Expression Analysis

Denoise expression matrix

Description

This function constructs and uses a neural network to denoise expression levels spatially.

Usage

runAutoencoderDenoising(
  object,
  activation = "relu",
  bottleneck = 56,
  mtr_name_output = "denoised",
  layers = c(128, 64, 32),
  dropout = 0.1,
  epochs = 20,
  display_plot = FALSE,
  genes = NULL,
  set_as_active = FALSE,
  verbose = TRUE,
  of_sample = NA
)

Arguments

object	An object of class SPATA2 or, in case of S4 generics, objects of classes for which a method has been defined.
activation	Character value. Denotes the activation function. (defaults to 'relu')
bottleneck	Numeric value. Denotes the number of bottleneck neurons.
mtr_name_output	Character value. Denotes the name under which the denoised matrix is stored in the data slot.
layers	Numeric vector of length 3. Denotes the number of neurons in the three hidden layers. (default = c(128, 64, 32))
dropout	Numeric value. Denotes the dropout. (defaults to 0.1)
epochs	Numeric value. Denotes the epochs of the neural network. (defaults to 20)
display_plot	Logical. If set to TRUE a scatter plot of the result is displayed in the viewer pane. See documentation for plotAutoencoderResults() for more information.
genes	Character vector of length two. Denotes the genes to be used for the validation plot.
set_as_active	Logical. If set to TRUE the denoised matrix is set as the active matrix via setActiveExpressionMatrix().
verbose	Logical. If TRUE, informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)

Value

A spata-object containing the denoised expression matrix in slot @data$denoised. This matrix is then denoted as the active matrix.

theMILOlab/SPATA2 documentation built on Feb. 8, 2025, 11:41 p.m.