Description Usage Arguments Details Value Author(s) References See Also Examples
Simulate data sets meant to emulate gene expression data in oncology.
1 2 3 | 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)
|
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. |
Simulates case/control data as described in createCase
and createControl
, and graphical domain knowledge as described in createGraph
.
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
).
Michelle Saul
ADD REFERENCE
createCase
, createControl
, createGraph
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## 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
|
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