man/gps-methods.Rd
 6fe809cf  \name{gps-methods} \docType{methods} \alias{gps} \alias{gps-methods} \alias{gps,RtreemixModel,RtreemixData-method} \alias{gps,RtreemixModel,matrix-method} \alias{gps,RtreemixModel,missing-method}  d0598af5   6fe809cf  \title{Methods for predicting the GPS of given dataset by using a given mutagenetic trees mixture model} \description{ These functions compute the genetic progression score (GPS) of each sample in the given \code{data} by performing a waiting time simulation along the branchings of the mixture model \code{model}. The model has to be specified. If a dataset is missing a GPS for all possible patterns is calculated. The number of events of the samples in \code{data} equals the number of genetic events in the \code{model}. } \usage{  ca550c24  gps(model, data, \dots)  6fe809cf  } \section{Methods}{\describe{  d0598af5  \item{model = "RtreemixModel", data = "RtreemixData", ...}{A method for calculating  6fe809cf  the GPS values of the data given as \code{RtreemixData} object.}  d0598af5  \item{model = "RtreemixModel", data = "matrix", ...}{A method for calculating  6fe809cf  the GPS values of the data given as 0-1 \code{matrix}.}  d0598af5  \item{model = "RtreemixModel", data = "missing", ...}{A method for calculating  6fe809cf  the GPS values of the set of all possible patterns.} }} \arguments{ \item{model}{An object of the class \code{RtreemixModel} specifying  432dbcff  the mutagenetic trees mixture model used for deriving the GPS values. The model should NOT have more than 20 genetic events.}  6fe809cf  \item{data}{An \code{RtreemixData} object or a 0-1 \code{matrix} containing the samples (patterns of genetic events) for which the GPS values are to be calculated. The length of each of them has to be equal to the number of genetic events in the \code{model}.}  ca550c24  \item{\dots}{ \code{sampling.mode} is a \code{character} that specifies the  6fe809cf  sampling mode ("constant" or "exponential") used in the waiting time  ca550c24  simulations. Its default value is "exponential". \code{sampling.param} is a \code{numeric} that specifies the  6fe809cf  sampling parameter corresponding to the sampling mode given by  ca550c24  \code{sampling.mode}. Its default value is 1. \code{no.sim} is an \code{integer} larger than 0 giving the number of iterations for the waiting time simulations. Its default value is 10. \code{seed} is a positive \code{integer} specifying the random generator  6fe809cf  seed. Its default value is (-1) and then the time is used as a  ca550c24  random generator. }  6fe809cf  } \value{ The function returns an object from the \code{RtreemixGPS} class that  d0598af5  containes the calculated GPS values, the model used for the  6fe809cf  computation, the data, and so on (see \code{\link{RtreemixGPS-class}}). The GPS values are represented as a \code{numeric} vector with length equal to the number of samples in \code{data}. } \references{Estimating cancer survival and clinical outcome based on genetic tumor progression scores, J. Rahnenf\"urer et al. } \note{  432dbcff  The mixture model used for deriving the GPS values should not have more than 20 genetic events. The reason for this is that the number of all possible patterns for which the GPS values are calculated during a computationally intensive simulations  ca550c24  is in this case $2^20$. This demands too much memory.  6fe809cf  The GPS examples are time consuming. They are commented out because of the time restrictions of the check of the package. For trying out the code please copy it and uncomment it. } \author{Jasmina Bogojeska} \seealso{ \code{\link{RtreemixGPS-class}}, \code{\link{RtreemixData-class}}, \code{\link{RtreemixModel-class}}, \code{\link{fit-methods}}, \code{\link{confIntGPS-methods}} } \examples{ ## Create an RtreemixData object from a randomly generated RtreemixModel object. #rand.mod <- generate(K = 2, no.events = 7, noise.tree = TRUE, prob = c(0.2, 0.8)) #data <- sim(model = rand.mod, no.draws = 400) ## Create an RtreemixModel object by fitting model to the given data. #mod <- fit(data = data, K = 2, equal.edgeweights = TRUE, noise = TRUE) #show(mod) ## Create an RtreemixGPS object by calculating the GPS for all possible patterns.  d0598af5  #modGPS.all <- gps(model = mod, no.sim = 1000) ## time consuming copmutations  6fe809cf  #show(modGPS.all) ## See the GPS values for all possible data.  d0598af5  #GPS(modGPS.all) ## time consuming copmutations  6fe809cf  ## 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)  d0598af5  #show(modGPS) ## time consuming copmutations  6fe809cf  ## See the GPS values for data.  d0598af5  #GPS(modGPS) ## time consuming copmutations  6fe809cf  }  d0598af5   6fe809cf  \keyword{methods} \keyword{survival}