04-plasmaPredictions-class: Class '"plasmaPredictions"'

In plasma: Partial LeAst Squares for Multiomic Analysis

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 plasmaPredictions class for plotting the Kaplan-Meier curves.
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 original outcome 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 for link{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 for link{coxph}.

SF:

Object of type survfit which is used by the plot method to plot Kaplan-Meier curves grouped by predicted Split. See documentation for link{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 [e-mail], Kyoko Yamaguchi [e-mail]

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)")

plasma documentation built on May 9, 2025, 3:01 a.m.