get_random_structure: Compute structure of dependency from a given data

In dependentsimr: Simulate Omics-Scale Data with Dependency

Compute structure of dependency from a given data

Description

Compute structure of dependency from a given data

Usage

get_random_structure(datasets, method, rank = 2, types = "normal")

Arguments

datasets	A list of data matrices that we will mimic. All datasets have samples in the columns and features (e.g., genes, proteins) in the rows. All datasets must have the same samples in corresponding columns.
method	One of 'pca', 'spiked Wishart', or 'corp.cor', for the method of determining a dependency structure
rank	Number of PCA components to approximate the dependence structure of. Only used if method = 'pca'.
types	The marginal distribution types ('normal', 'poisson', 'DESeq2', or 'empirical'), as a list with entries corresponding to datasets. If just a single value is provided, then it is used for all datasets.

Value

A random structure element suitable for use with draw_from_multivariate_corr().

Examples

# Simple data to mimic
true_means <- c(0, 1, 10, 1000)
data <- rpois(4*12, true_means) |> matrix(4, 12)

# Simulate draws mimicking that data
rs <- get_random_structure(list(data=data), method="pca", rank=2, type="poisson")
draws <- draw_from_multivariate_corr(rs, n_samples=30)

dependentsimr documentation built on Aug. 8, 2025, 6:23 p.m.