simulate_expression_pattern_sas: Expression pattern simulation
In theMILOlab/SPATA2: A Toolbox for Spatial Expression Analysis

simulate_expression_pattern_sas

R Documentation

Expression pattern simulation

Description

Simulates expression patterns by modelling expression dependent on the distance to a spatial annotation.

Usage

simulate_expression_pattern_sas(
  object,
  ids,
  simulations,
  core,
  distance = "dte",
  resolution = recSgsRes(object),
  angle_span = c(0, 360),
  noise_levels = seq(0, 100, length.out = 21),
  noise_types = c("ed", "ep", "fp", "cb"),
  range_sim = c(0, 1),
  range_random = base::range(range_sim),
  model_add = NULL,
  model_remove = NULL,
  seed = 123,
  npref = "SE",
  nsep = ".",
  verbose = TRUE
)

simulate_expression_pattern_sts(
  object,
  id,
  simulations,
  width,
  resolution = recSgsRes(object),
  noise_levels = seq(0, 100, length.out = 21),
  noise_types = c("ed", "ep", "fp", "cb"),
  range_sim = c(0, 1),
  range_random = base::range(range_sim),
  model_add = NULL,
  seed = 123,
  npref = "SE",
  nsep = ".",
  verbose = TRUE
)

simulate_random_expression(
  object,
  n_total,
  range_sim = c(0, 1),
  seed = 123,
  naming = "SE.RANDOM.{i}",
  verbose = TRUE
)

Arguments

`object`	An object of class `SPATA2` or, in case of S4 generics, objects of classes for which a method has been defined.
`ids`	Character vector. Specifies the IDs of the spatial annotations of interest.
`simulations`	A list of simulation lists. A simulations list is a list that contains at least three slots that provide instructions for a set of simulations: id Character value. The overall ID of the simulation. n Integer. The number of simulations. model Character value. The name of the model based on which you want to simulate the expression. A simulation list can have an additional slot called noise_levels which, if present, overwrites the input for `noise_levels` for the specific simulation.
`distance`	`Distance measure`. Specifies the distance from the border of the spatial annotation to the horizon in the periphery up to which the screening is conducted. Defaults to a distance that covers the whole tissue section the spatial annotation is located on using `distToEdge()`. (This distance must not be exceeded.)
`resolution`	Distance measure. The resolution with which the expression gradient is inferred. Defaults are platform specific. See more in detail section of `recSgsRes()`.
`angle_span`	Numeric vector of length 2. Confines the area screened by an angle span relative to the center of its closest spatial annotation.
`noise_levels`	A vector of integers between 0-100 (inclusive). Indicate the respective levels of noise to be added to each simulation in percent. 0 indicates no noise. 100 indicates only noise.
`range_sim`	The range of the output simulation values.
`range_random`	The range of the values randomly assigned to areas outside of the area of interest.
`model_add`	Named list. Every slot in the list must be either a formula containing a function that takes a numeric vector as input and returns a numeric vector with the same length as its input vector. Or a numeric vector with the same length as the input vector. Test models with `showModels()`.
`model_remove`	Character value. Used as a regex to remove models are not supposed to be included.
`seed`	Numeric value, given to `set.seed()`.
`npref`	Prefix for the simulations. Defaults to SG (simulated gene.)
`nsep`	Character value with which to separate the aspects that build the name of each simulation.
`verbose`	Logical. If `TRUE`, informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)

Details

Simulation names are created according to the function call stringr::str_c(npref, nsep, "NP", nl, nsep, sim_id, nsep, n, sep = ""). Where nl is the noise level of the simulation, sim_id corresponds to the slot id of the simulation list and n is the index of the simulation in case slot n of the simulation instruction is bigger than one.