simulate_data {MOSS}

Simple simulation of regulatory modules.

Description

This a simple simulation to use in MOSS' examples. The specifics of the simulation are shown in the "Examples" section.

Usage

simulate_data(moss_seed = 42)

Arguments

moss_seed

The seed for random number generator. Numeric. Defaults to 42.

Value

A list of two elements 'sim_blocks' and 'labels'. First element 'sim_blocks' is a list of three numeric matrices, and one character matrix. Second element 'labels' has two character vectors. The first element 'lab.sub' identifies the groups of 'signal' subjects. The second element 'lab.feat' identifies the groups 'signal' features from background 'noise'.

Examples

sim_data <- simulate_data()

# Extracting simulated omic blocks.
sim_blocks <- sim_data$sim_blocks

# Extracting subjects and features labels.
lab.sub <- sim_data$labels$lab.sub
lab.feat <- sim_data$labels$lab.feat

# Check dimensions and objects class.
lapply(sim_blocks, dim)
lapply(sim_blocks, function(x) class(x[, 1]))

# Showing how the data was generated.
set.seed(42)
O1 <- matrix(data = 0, nrow = 5e2, ncol = 1e3)
O2 <- O1
O1[1:20, 1:150] <- 1
O1 <- O1 + rnorm(5e5, mean = 0, sd = 0.5)
O2[71:90, 71:200] <- 1
O2 <- O2 + rnorm(5e5, mean = 0, sd = 0.5)
# Simulating a continous response blocks.
O3 <- 3 * O1 - 5 * O2 + rnorm(5e5, mean = 0, sd = 0.5)

# Creating a vector labeling clusters of subjects.
aux <- rep("Background", 500)
aux[1:20] <- "Group 1"
aux[71:90] <- "Group 2"
all.equal(aux, lab.sub)

# Generating a classification response.
O4 <- as.matrix(aux)

# Storing all blocks within a list.
all.equal(sim_blocks, list(
  "Block 1" = O1,
  "Block 2" = O2,
  "Block 3" = O3,
  "Block 4" = O4
))

# Creating a vector labeling signal and background features.
aux <- rep("Background features", 3000)
aux[c(1:150, 1072:1200, 2001:2200)] <- "Signal features"
all.equal(aux, lab.feat)