Rtreemix (version 1.34.0)

RtreemixGPS-class: Class "RtreemixGPS"

Description

A class for describing the genetic progression scores (GPS) of a given set of patterns resulting from a waiting time simulation along the edges of the tree components of a given mutagenetic trees mixture model. It also contains GPS confidence intervals derived with the bootstrap method.

Objects from the Class

Objects can be created by calls of the form new("RtreemixGPS", Data, Model, SamplingMode, SamplingParam, GPS, gpsCI). The RtreemixGPS class contains the GPS values each assigned to the corresponding pattern from the dataset given by Data (the parent class). The GPS values are derived in a waiting time simulation for a specified sampling mode and its corresponding sampling parameter. Moreover, this class specifies the confidence intervals for the GPS values derived with the bootstrap method. The Data is an RtreemixData object that specifies the patterns for which the GPS values are calculated. The Model is an RtreemixModel object that specifies the mutagenetic trees mixture model used for deriving the GPS values. The SamplingMode is a character that specifies the sampling mode ("constant" or "exponential") used in the waiting time simulations. The SamplingParam is a numeric that specifies the sampling parameter corresponding to the sampling mode given by SamplingMode. The GPS is a numeric vector that specifies the GPS value of each pattern in the given dataset Data. Its length equals the number of patterns in Data. The gpsCI is a numeric matrix that specifies the confidence intervals for each GPS value in the vector GPS. The number of rows equals the number of patients in Data and the number of columns equals 2. The first column gives the lower bound and the second column gives the upper bound of each confidence interval.

Slots

Model:

Object of class "RtreemixModel".

SamplingMode:

Object of class "character". It can have one of the two possible values: "constant" or "exponential".

SamplingParam:

Object of class "numeric".

GPS:

Object of class "numeric". The length of GPS must be equal to the number of patterns in the parent RtreemixData object.

gpsCI:

Object of class "matrix". It number of columns has to be 2 and the number of rows has to be equal to the length of GPS.

Extends

Class "RtreemixData", directly.

Methods

GPS

signature(object = "RtreemixGPS"): A method for obtaining the GPS values corresponding to the patterns in the parent RtreemixData object.

Model

signature(object = "RtreemixGPS"): A method for obtaining the model used for deriving the GPS values.

SamplingMode

signature(object = "RtreemixGPS"): A method for obtaining the sampling mode ("constant" or "exponential") used for the waiting time simulations.

SamplingParam

signature(object = "RtreemixGPS"): A method for obtaining the sampling parameter corresponding to the specified SamplingMode.

getData

signature(object = "RtreemixGPS"): A method for obtaining the set of patterns for which the GPS values are calculated.

gpsCI

signature(object = "RtreemixGPS"): A method for obtaining the GPS confidence intervals.

References

Estimating cancer survival and clinical outcome based on genetic tumor progression scores, J. Rahnenf\"urer et al.

See Also

RtreemixData-class, RtreemixModel-class, gps-methods, fit-methods, confIntGPS-methods

Examples

## Generate a random RtreemixModel object with 3 components and 9 genetic events.
#mod <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob = c(0.2, 0.8))
#show(mod)
## Generate an artificial dataset from the model mod.
#data <- sim(model = mod, no.draws = 300)
#show(data)

## Create an RtreemixGPS object by calculating the GPS for all possible patterns.
#modGPS.all <- gps(model = mod, no.sim = 1000)
#show(modGPS.all)
## Create an RtreemixGPS object by calculating the GPS for the data based on the model mod.
#modGPS <- gps(model = mod, data = data, no.sim = 1000)
#show(modGPS)

## See the slots from the RtreemixGPS object. 
#Model(modGPS)
#SamplingMode(modGPS)
#SamplingParam(modGPS)
#GPS(modGPS)
## See data.
#getData(modGPS)

## Create an RtreemixGPS object by calculating GPS values for a given dataset
## and their 95% confidence intervals using the bootstrap method.
#modGPS2 <- confIntGPS(data = data, K = 2, B = 10)
#show(modGPS2)

## See the GPS values for the object modGPS2 and their confidence intervals.
#GPS(modGPS2)
#gpsCI(modGPS2)