MetaDE (version 1.0.5)

MetaDE.Read: Read data sets into R

Description

Function to import data set(s) into R and reformat it (them) to form required for other functions in MetaDE package.

Usage

MetaDE.Read(filenames, via = c("txt", "csv"), skip,matched=FALSE, log = TRUE)

Arguments

filenames
a character vecter specifying the names of data sets to read data values from. Should be a tab-separated or comma-separated text file, with one row per gene set.
via
a character to specify the type of data sets. "txt" means tab delimited files and "csv" means comma-delimited files.
skip
a vecter of size K (the number of data sets) composes of 1 or 2. see 'Details'.
matched
a logical to specify whether the gene ProbeIDs have been matched into gene symbols in each data set.
log
a logical to specify wheter data sets need to be log2-transformed.

Value

  • a list of studies. Each study is a list with components:
    • x: the gene expression matrix.
    • y: the outcome.
    • censoring.status: the censoring status. This only for survival data.
    • symbol: the gene symbols. This is only for un-matched raw data.

Details

The files to be read in should be prepared strictly according following format: If matched is FALSE, column 1 has gene ProbeIds, column 2 has gene symbols, remaining columns are samples. If matched is TRUE, column 1 has gene symbols, remaining columns are samples. If the data set is a survival data, the second row should has the survival time,and third row should have the status of events,and remaining rows are gene expression files . otherwise, the second row should has the labels of samples and remaing rows are gene expression profiles. If the ith file is a survival data,the corresponding element of skip should be 2, otherwise, 1. The user can prepare the files according the structure of files wrote out using the example file.

References

Xingbin Wang, Jia Li and George C Tseng. Conducting Meta-analysis in R with the MetaDE package. http:xxxxx/MetaDE.pdf

See Also

MetaDE.match, MetaDE.rawdata

Examples

Run this code
#================example test MetaDE.Read ==================================================#
setwd(tempdir())
label1<-rep(0:1,each=5)
label2<-rep(0:1,each=5)
exp1<-cbind(matrix(rnorm(5*20),20,5),matrix(rnorm(5*20,2),20,5))
exp2<-cbind(matrix(rnorm(5*20),20,5),matrix(rnorm(5*20,1.5),20,5))
rownames(exp1)<-paste("g1",1:20,sep="_")
rownames(exp2)<-paste("g2",1:20,sep="_")
study1<-rbind(label1,exp1)
study2<-rbind(label2,exp2)
write.table(study1,"study1.txt",sep="t")
write.table(study1,"study2.txt",sep="t")
mydata<-MetaDE.Read(c("study1","study2"),via="txt",skip=rep(1,2),matched=TRUE,log=FALSE)
#================Non-matched  =============================================================#
label1<-rep(0:1,each=5)
label2<-rep(0:1,each=5)
exp1<-cbind(matrix(rnorm(5*20),20,5),matrix(rnorm(5*20,2),20,5))
exp2<-cbind(matrix(rnorm(5*20),20,5),matrix(rnorm(5*20,1.5),20,5))
rownames(exp1)<-paste("g1",1:20,sep="_")
rownames(exp2)<-paste("g2",1:20,sep="_")
symbol1<-sample(c("SST","VGF","CNP"),20,replace=TRUE)
symbol2<-sample(c("SST","VGF","CNP"),20,replace=TRUE)
study1<-cbind(c(NA,symbol1),rbind(label1,exp1))
study2<-cbind(c(NA,symbol2),rbind(label2,exp2))
setwd(tempdir())
write.table(study1,"study1.txt",sep="t")
write.table(study2,"study2.txt",sep="t")
mydata<-MetaDE.Read(c("study1","study2"),via="txt",skip=rep(1,2),log=FALSE)

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