cvmm-class: The cvmm Class.

In OlajumokeEvangelina/MetabolicSurv: A Biomarker Validation Approach for Classification and Predicting Survival Using Metabolomics Signature

Description

Class of object returned by function CVMetSpecificCoxPh.

Usage

## S4 method for signature 'cvmm'
show(object)

## S4 method for signature 'cvmm'
summary(object, which = 1)

## S4 method for signature 'cvmm,ANY'
plot(x, y, which = 1, ...)

Arguments

object	A CVMetSpecificCoxPh class object
which	This specify which metabolite for which estimated HR information need to be visualized. By default results of the first metabolite is used.
x	A CVMetSpecificCoxPh class object
y	missing
...	The usual extra arguments to generic functions — see plot, plot.default

Details

plot signature(x = "cvmm"): Plots for CVMetSpecificCoxPh class analysis results.

Any parameters of plot.default may be passed on to this particular plot method.

Slots

HRTrain

A 3-way array, The first dimension is the number of metabolites, the second dimension is the HR statistics for the low risk group in the train dataset (HR,1/HR LCI, UCI) while the third dimension is the number of cross validation performed.

HRTest

A 3-way array, The first dimension is the number of metabolites, the second dimension is the HR statistics for the low risk group in the test dataset (HR,1/HR LCI, UCI) while the third dimension is the number of cross validation performed.

train

The selected subjects for each CV in the train dataset

test

The selected subjects for each CV in the test dataset

n.mets

The number of metabolite used in the analysis

Ncv

The number of cross validation performed

Rdata

The Metabolite data matrix that was used for the analysis either same as Mdata or a reduced version

Author(s)

Olajumoke Evangelina Owokotomo, [e-mail]

Ziv Shkedy

See Also

CVMetSpecificCoxPh

Examples

## GENERATE SOME METABOLIC SURVIVAL DATA WITH PROGNOSTIC FACTORS
Data<-MSData(nPatients=100,nMet=150,Prop=0.5)

## USING THE FUNCTION
Result = CVMetSpecificCoxPh(Fold=3,Survival=Data$Survival,
Mdata=t(Data$Mdata),Censor= Data$Censor,Reduce=TRUE,
Select=150,Prognostic=Data$Prognostic,Quantile = 0.5,Ncv=3)

## GET THE CLASS OF THE OBJECT
class(Result)     # An "cvmm" Class

##  METHOD THAT CAN BE USED FOR THIS CLASS
show(Result)
summary(Result)
plot(Result)

OlajumokeEvangelina/MetabolicSurv documentation built on Aug. 7, 2019, 1:06 p.m.