TCGA2STAT (version 1.0)

GeneMerge: Merge Data of Two Types of Molecular Profiles.

Description

Combine the data matrix of two types of molecular profiles for the same tumor samples.

Usage

GeneMerge(dat1, dat2)

Arguments

dat1

data matrix in gene x sample format.

dat2

data matrix in gene x sample format.

Value

• A list of three elements:
• merged.data
  a matrix in sample x gene format
• X
  a matrix in sample x "gene from dat1" format with samples in the same order as Y
• Y
  a matrix of size sample x "gene from dat2" format with sampels in the same order as X

Details

This function combines data matrices of two types of molecular profiles for the same set of tumor samples in the correct patient order. The number of genes returned is the sum of genes from two input matrices; the number of samples returned will be the tumor samples common to both input matrices. Gene names in the returned data will be suffixed by "d1" or "d2" to indicate if the gene is from the first or the second input matrix.

Examples

#	Here is a brief example of how to merge methylation and gene expression (RNASeq) data
#	and use the data for CCA analysis

library(TCGA2STAT)

lusc.methyl <- getTCGA(disease="LUSC", data.type="Methylation", clinical=FALSE)
lusc.rnaseq2 <- getTCGA(disease="LUSC", data.type="RNASeq2")

met.var <- apply(lusc.methyl[,-c(1,2,3)], 1, var)
met.data <- subset(lusc.methyl[,-c(1,2,3)], met.var >= quantile(met.var, 0.99, na.rm=TRUE) 
                & !is.na(met.var))

rnaseq2.var <- apply(log10(1+lusc.rnaseq2$dat), 1, var)
rnaseq.data <- subset(log10(1+lusc.rnaseq2$dat), 
                rnaseq2.var >= quantile(rnaseq2.var, 0.99, na.rm=TRUE) 
                & !is.na(rnaseq2.var))

met.rnaseq2 <- GeneMerge(dat1 = rnaseq.data, dat2= met.data)
library(CCA)
estl <- estim.regul(met.rnaseq2$X, met.rnaseq2$Y)
lusc.cc <- rcc(met.rnaseq2$X, met.rnaseq2$Y, estl$lambda1, estl$lambda1)
plt.cc(lusc.cc, d1=1, d2=2, type="b", var.label=TRUE)