03-manyCoxModels: Class '"MultiplePLSCoxModels"'

In plasma: Partial LeAst Squares for Multiomic Analysis

Class "MultiplePLSCoxModels"

Description

The MultiplePLSCoxModels object class ... The validMultipleCoxModels function checks if each data set contains the same set of samples. The fitCoxModels function fits many plsRcoxmodels and returns an S4 object of class MultiplePLSCoxModels. The getSizes function returns a matrix with the list of dataframes of the MultiOmics object as rownames and columns with NT, cNT, and p-values.

Usage

fitCoxModels(multi, timevar, eventvar, eventvalue, verbose)
## S4 method for signature 'MultiplePLSCoxModels'
summary(object, ...)
## S4 method for signature 'MultiplePLSCoxModels,missing'
plot(x, y, col = c("blue", "red"),
      lwd = 2, xlab = "", ylab = "Fraction Surviving",
       mark.time = TRUE, legloc = "topright", ...)
## S4 method for signature 'MultiplePLSCoxModels'
predict(object, newdata, type = c("components", "risk",
                 "split", "survfit"), ...)

Arguments

multi	an object of class MultiOmics for fitting the model.
timevar	a column in the MultiOmics object in the outcome dataframe containing the time-to-event.
eventvar	a column in the MultiOmics object in the outcome dataframe containing the event.
eventvalue	a character string specifying the value of the event in eventvar.
verbose	logical; should the function report progress.
object	an object of class MultiplePLSCoxModels for outputting the summary.
x	an object of class MultiplePLSCoxModels for plotting the Kaplan-Meier curves.
y	An ignored argrument for the plot method.
col	A vector of color specifications. Default is c(“blue”, “red”).
lwd	A vector 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.
newdata	A MultiOmics object with the same structure as the training data.
type	An enumerated character value.

Value

The fitCoxModels function retuns a newly constructed object of the MultiplePLSCoxModels class. The plot method invisibly returns the object on which it was invoked. The summary method returns no value. The predict method returns a list of prediction results, each of which comes from the predict method for the SingleModel-class.

Slots

models:

A list of SingleModel objects, one for each assay.

timevar:

A character matching the name of the column containing the time-to-event.

eventvar:

A character matching the name of the column containing the event.

eventvalue:

A character specifying the event in eventvar.

Methods

plot:

Plots Kaplan-Meier curves for each omics dataset split into Low Risk and High Risk groups.

summary:

Returns a description of the MultiplePLSCoxModels object and the names of the omics datasets used to build the model.

predict:

usually returns a list of numeric vectors of predicted risk per data type. When type = "survfit", retuns a list of survfit objects.

Author(s)

Kevin R. Coombes [e-mail], Kyoko Yamaguchi [e-mail]

See Also

fitSingleModel

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")

summary(firstPass)
plot(firstPass)
getSizes(firstPass)
pre1 <- predict(firstPass, testD)

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