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Old 05-06-2014, 01:09 AM   #1
willemate
Junior Member
 
Location: Berlin

Join Date: Mar 2014
Posts: 9
Question Correlation Plots

Dear All,

Im am working on a comparison study, I used Limma and DESeq to get the DEGs at 3 different timepoints, 13989 genes.
Microarray data: 8 samples (d0d1d3d6d0d1d3d6), rnaseq data: 9 samples (d0d0d0d1d1d3d3d6d6).

I would like to make correlation plots to compare the deferentially expression for each gene and the means between the rnaseq and microarray data. I would like to get correlation plots with the correlation coefficient (y-axis) and the mean expression (x-axis) of my microarray data, rnaseq data and compared.
Below you see my data. Can anybody help me to get started on this.

## data
rnaseq <- read.table("rnaseq.data.csv", sep=",", row.names=2,header=T)
ma <- read.table("results.txt", header = TRUE, sep = "\t", row.names=1)

> dim(rnaseq)
[1] 13989 15
> dim(ma)
[1] 13989 22

# Correlation of the RNA-Seq means
rnaseq.mean.cor <- cor(rnaseq[c(3, 4, 5, 6)])
> rnaseq.mean.cor
d0mean d1mean d3mean d6mean
d0mean 1.0000000 0.2882263 0.4246321 0.3392603
d1mean 0.2882263 1.0000000 0.7513139 0.6459144
d3mean 0.4246321 0.7513139 1.0000000 0.9496546
d6mean 0.3392603 0.6459144 0.9496546 1.0000000

## Correlation of the microarray means
ma.mean.cor <- cor(ma[c(10, 11, 12, 13)])
> ma.mean.cor
d0mean d1mean d3mean d6mean
d0mean 1.0000000 0.5614268 0.6269302 0.6293948
d1mean 0.5614268 1.0000000 0.8600314 0.7722005
d3mean 0.6269302 0.8600314 1.0000000 0.9618639
d6mean 0.6293948 0.7722005 0.9618639 1.0000000

## qplot RNA-Seq
rnaseq.d0d1.qplot <- qplot(data=rnaseq,x=d0mean,y=d1mean,log="xy", main = "qplot RNA-Seq d0mean-d1mean")
rnaseq.d0d3.qplot <- qplot(data=rnaseq,x=d0mean,y=d3mean,log="xy", main = "qplot RNA-Seq d0mean-d3mean")
rnaseq.d0d6.qplot <- qplot(data=rnaseq,x=d0mean,y=d6mean,log="xy", main = "qplot RNA-Seq d0mean-d6mean")

## qplot microarray
ma.d0d1.qplot <- qplot(data=ma,x=d0mean,y=d1mean,log="xy", main = "qplot microarray d0mean-d1mean")
ma.d0d3.qplot <- qplot(data=ma,x=d0mean,y=d3mean,log="xy", main = "qplot microarray d0mean-d3mean")
ma.d0d6.qplot <- qplot(data=ma,x=d0mean,y=d6mean,log="xy", main = "qplot microarray d0mean-d6mean")

Thank you for your help!

Mossevelde
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bioconductor, correlation, microarray, rna-seq, rstudio

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