rowCoxTests: rowCoxTests

In simulatorZ: Simulator for Collections of Independent Genomic Data Sets

Description

method for performing Cox regression

Usage

rowCoxTests(X, y, option = c("fast", "slow"), ...)

Arguments

X	Gene expression data. The following formats are available: matrix Rows correspond to observations, columns to variables. data.frame Rows correspond to observations, columns to variables. ExpressionSet rowCoxTests will extract the expressions using exprs().
y	Survival Response, an object of class: Surv if X is of type data.frame or matrix character if X is of type ExpressionSet. In this case y is the name of the survival response in the phenoData of X. If survival time and indicator are stored separately in the phenoData one can specify a two-element character vector the first element representing the survival time variable.
option	"fast" loops over rows in C, "slow" calls coxph directly in R. The latter method may be used if something goes wrong with the "fast" method.
...	currently unused

Value

dataframe with two columns: coef = Cox regression

coefficients, p.value =

Wald Test p-values. Rows correspond to the rows of X.

Author(s)

Yuqing Zhang, Christoph Bernau, Levi Waldron

Examples

#test


##regressor-matrix (gene expressions)


X<-matrix(rnorm(1e6),nrow=10000)


#seed


set.seed(123)


#times


time<-rnorm(n=ncol(X),mean=100)


#censoring(1->death)


status<-rbinom(n=ncol(X),size=1, prob=0.8)





##survival object


y<-Surv(time,status)





## Do 10,000 Cox regressions:


system.time(output <- rowCoxTests(X=X,y=y, option="fast"))

simulatorZ documentation built on Nov. 8, 2020, 5 p.m.