OmixCraftHD {SUMO} | R Documentation |
Simulation of high-dimensional data with predefined single factor or multiple factors in multi-omics
OmixCraftHD(
vector_features = c(2000, 2000),
n_samples = 50,
sigmas_vector = c(3, 5),
n_factors = 3,
num.factor = "multiple",
advanced_dist = NULL
)
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' |
A list containing:
dataset_1
: A matrix or data frame representing the first simulated dataset with rows as samples and columns as features.
dataset_2
: A matrix or data frame representing the second simulated dataset with rows as samples and columns as features.
factors
: A matrix representing the predefined factors used in generating the datasets. If num.factor
is 'single', this contains one set of factors. If num.factor
is 'multiple', it contains multiple sets of factors.
noise
: A list containing the noise terms added to both datasets based on the sigmas_vector
.
factor_assignment
: A vector indicating how factors are assigned to datasets, depending on the num.factor
and advanced_dist
settings.
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:
dataset_1
: A matrix or data frame representing the first simulated dataset with rows as samples and columns as features.
dataset_2
: A matrix or data frame representing the second simulated dataset with rows as samples and columns as features.
factors
: A matrix representing the predefined factors used in generating the datasets. If num.factor
is 'single', this contains one set of factors. If num.factor
is 'multiple', it contains multiple sets of factors.
noise
: A list containing the noise terms added to both datasets based on the sigmas_vector
.
factor_assignment
: A vector indicating how factors are assigned to datasets, depending on the num.factor
and advanced_dist
settings.
The output provides simulated multi-omics datasets with predefined latent factors and noise, which can be used to model complex biological data structures.
# 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
)