FamilyRank (version 1.0)

createData: Simulate Data

Description

Simulate data sets meant to emulate gene expression data in oncology.

Usage

createData(n.case, n.control, mean.upper = 13, mean.lower = 5, 
sd.upper = 1, sd.lower = 1, n.features = 10000, 
subtype1.feats = 1:5, subtype2.feats = 6:10, subtype3.feats = 11:15)

Arguments

n.case

Number of cases to simulate.

n.control

Number of controls to simulate

mean.upper

Mean of upper component of bimodal Gaussian distribution from which features are simulated.

mean.lower

Mean of lower component of bimodal Gaussian distribution from which features are simulated.

sd.upper

Standard deviation of upper component of bimodal Gaussian distribution from which features are simulated.

sd.lower

Standard deviation of lower component of bimodal Gaussian distribution from which features are simulated.

n.features

Number of features to simulate

subtype1.feats

Index of features used to define subtype 1.

subtype2.feats

Index of features used to define subtype 2.

subtype3.feats

Index of features used to define subtype 3.

Value

Returns a named list with a simulated feature matrix (x), simulated binary response vector (y), vector of subtype labels (subtype), and simulated domain knowledge graph (graph).

Details

Simulates case/control data as described in createCase and createControl, and graphical domain knowledge as described in createGraph.

References

ADD REFERENCE

See Also

createCase, createControl, createGraph

Examples

# NOT RUN {
## Toy Example
# Simulate data set
# 10 samples
# 20 features
# Features 1 through 15 perfectly define response
# All other features are random noise.
data <- createData(n.case = 5, n.control = 5, mean.upper=13, mean.lower=5,
                   sd.upper=1, sd.lower=1, n.features = 20,
                   subtype1.feats = 1:5, subtype2.feats = 6:10,
                   subtype3.feats = 11:15)
x <- data$x
y <- data$y
graph <- data$graph
# }