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#1 |
Junior Member
Location: Berlin Join Date: Mar 2014
Posts: 9
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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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