OmixCraftHD {SUMO}R Documentation

Simulation of high-dimensional data with predefined single factor or multiple factors in multi-omics

Description

Simulation of high-dimensional data with predefined single factor or multiple factors in multi-omics

Usage

OmixCraftHD(
  vector_features = c(2000, 2000),
  n_samples = 50,
  sigmas_vector = c(3, 5),
  n_factors = 3,
  num.factor = "multiple",
  advanced_dist = NULL
)

Arguments

vector_features

Vector of features assigned to the two simulated datasets respectively '1' first dataset, '2' second dataset

n_samples

The number of samples common between the two simulated datasets

sigmas_vector

Vector for the noise variability for the two simulated datasets respectively, '1' first dataset, '2' second dataset

n_factors

Number of predefined factors

num.factor

Category of factors to be simulated specified as 'single', or 'multiple'.

advanced_dist

Applicable only when num.factor = 'multiple'. Contains six possible arguments, ”, NULL, 'mixed', 'omic.one', or 'omic.two', 'exclusive'

Value

A list containing:

The output provides simulated multi-omics datasets with predefined latent factors and noise, which can be used to model complex biological data structures.

A list containing:

The output provides simulated multi-omics datasets with predefined latent factors and noise, which can be used to model complex biological data structures.

Examples

# Examples
set.seed(1234)
output_obj <- OmixCraftHD(
  vector_features = c(2000,3000),
  sigmas_vector=c(8,5),
  n_samples=100,
  n_factors=5,
  num.factor='multiple',
  advanced_dist='mixed'
)
output_obj <- OmixCraftHD(
  vector_features = c(5000,3000),
  sigmas_vector=c(3,4),
  n_samples=30, n_factors=1
)


[Package SUMO version 0.1.0 Index]