plasmaPredictions-class {plasma} | R Documentation |
Class "plasmaPredictions"
Description
The plasmaPredictions
object class is returned when running the
predict
method on an object of class plasma
.
Usage
## S4 method for signature 'plasmaPredictions,missing'
plot(x, y, col = c("blue", "red"),
lwd = 2, xlab = "", ylab = "Fraction Surviving",
mark.time = TRUE, legloc = "topright", ...)
Arguments
x |
An object of the |
y |
An ignored argument for the plot method. |
col |
A vector of color specifications. Default is c(“blue”, “red”). |
lwd |
A vactor specifying the line width. Default is “2”. |
xlab |
A character string to label the x-axis. Default is “”. |
ylab |
A character string to label the y-axis. Default is “Fraction Surviving”. |
mark.time |
A logical value; should tickmarks indicate censored data? Default is TRUE. |
legloc |
A character string indicating where to put the legend. Default is “topright”. |
... |
Other graphical parameters. |
Value
The predict
method on an object of the plasma
class returns an object of the plasmaPredictions
class. The plot
method invisibly returns the value on which it
was invoked.
Objects from the Class
Users shold not create objects of this class directly. They will be
automatically created when you apply the predict
method to a
fully worked out plasma
model.
Slots
meanPredictions
:A matrix with samples as rows and factors as columns that is a result of taking the mean of the PLS component predictions from each dataset.
riskDF
:Object of type
data.frame
containing the originaloutcome
dataframe and additional columns for "Risk", and "Split", corresponding to the risk of the event calculated by the model, and patient assignment to low versus high-risk groups, respectively.riskModel
:Object of type
coxph
that uses predicted Risk (continuous) as the predictor variable and survival as the response variable. See documentation forlink{coxph}
.splitModel
:Object of type
coxph
that uses predicted Split (predicted Risk categorized into “high” and “low” risk by the median predicted Risk) as the predictor variable and survival as the response variable. See documentation forlink{coxph}
.SF
:Object of type
survfit
which is used by theplot
method to plot Kaplan-Meier curves grouped by predicted Split. See documentation forlink{survfit}
.
Methods
plot
:Produces Kaplan-Meier curves for the low risk and high risk groups.
Note
An object of plasmaPredictions
class contains many models that
are similar to an object of MultiplePLSCoxModels
class.
Author(s)
Kevin R. Coombes krc@silicovore.com, Kyoko Yamaguchi kyoko.yamaguchi@osumc.edu
See Also
plasma
Examples
fls <- try(loadESCAdata())
if (inherits(fls, "try-error")) {
stop("Unable to load data from remote server.")
}
# restrict data set size
MO <- with(plasmaEnv, prepareMultiOmics(
assemble[c("ClinicalBin", "ClinicalCont", "RPPA")], Outcome))
splitVec <- with(plasmaEnv, rbinom(nrow(Outcome), 1, 0.6))
trainD <- MO[, splitVec == 1]
testD <- MO[, splitVec == 0]
firstPass <- fitCoxModels(trainD, "Days", "vital_status", "dead")
pl <- plasma(object = trainD, multi = firstPass)
testpred <- predict(pl, testD)
plot(testpred, main = "Testing", xlab = "Time (Days)")