Map > Problem Definition > Data Preparation > Methylation
 

Data Preparation - Methylation

Methylation arrays enable quantitative interrogation of selected methylation sites across the genome, offering high-throughput capabilities that minimize the cost per sample.
 
GSE76105
Genome-wide DNA methylation profiling in the superior temporal gyrus reveals epigenetic signatures associated with Alzheimer's disease. This experiment's data can be downloaded using the following R code:
library(GEOquery)

# Experiment
dataset.id <- "GSE76105"
gse <- getGEO(dataset.id , GSEMatrix = TRUE)[[1]]
mat <- exprs(gse)
target <- pData(gse)
genes <- featureNames(gse)

# Samples
fname <- paste("c:\\temp\\" , dataset.id , "_targets.csv",sep="")
write.csv(target, file=fname, row.names=FALSE, quote=FALSE)

# Expressions
fname <- paste("c:\\temp\\" , dataset.id , "_expr.csv",sep="")
write.csv(mat, file=fname, row.names=TRUE, quote=FALSE)

# Probes
fname <- paste("c:\\temp\\" , dataset.id , "_probes.csv",sep="")
write.csv(genes,file=fname,row.names=TRUE,quote=FALSE)

# Expressions plot
boxplot(mat[,1:20])
 
Data Processing 
In order to follow one universal data model we create the following three files. Click on the file name to download the file.

 

Bioada SmartArray 
This video shows how you can upload the GSE76105 files to Bioada SmartArray and explore, visualize and build predictive models significantly faster and easier.