PCA analysis of the RNASeq data
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Emily • 0
@emily-8166
Last seen 9.4 years ago
United States

Hi everyone,

I am doing a PCA analysis with my RNASeq data and I want to konw whether the genotypes have a great effect on the gene expression. I have four genotypes :G0(wild type),G1,G2,G3 and three time points: T1,T2,T3. All the values in the dataset are Log2FC values compared to wild type. The data looks like this:

Gene  Genotype  T1   T2   T3
a1 G1 . . .
a2 G1 . . .
a3 G1 . . .
a4 G1 . . .
a5 G1 . . .
a6 G1 . . .
a7 G1 . . .
a8 G1 . . .
a9 G1 . . .
a10 G1 . . .
a1 G2 . . .
a2 G2 . . .
a3 G2 . . .
a4 G2 . . .
a5 G2 . . .
a6 G2 . . .
a7 G2 . . .
a8 G2 . . .
a9 G2 . . .
a10 G2 . . .
a1 G3 . . .
a2 G3 . . .
a3 G3 . . .
a4 G3 . . .
a5 G3 . . .
a6 G3 . . .
a7 G3 . . .
a8 G3 . . .
a9 G3 . . .
a10 G3 . .

.After the PCA analysis,

all the dots red, blue and green (represent three different genotypes ) are stacked together, they are not clustered according to genotypes. I am not sure this is what it is or there is something wrong with my data format.  

Thanks for your help in advance.

rnaseq R • 1.7k views
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What do the dots mean in your description of the data? What commands did you use to generate the PCA plot? Can you give us a picture of what the PCA plot actually looks like?

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Entering edit mode
Emily • 0
@emily-8166
Last seen 9.4 years ago
United States

Hi Aaron, thanks for your reply. The dot in my description of the data means the value, I did not give the actual value for each datapoint, just use dot instead.

The command I used to generate the PCA plot is as follows:

library(psych)
library(GPArotation)
data = read.table("C:\\Users\\Desktop\\PCA\\log2FC.csv", header=T, sep = ",")
attach(data)
str(data)
Datax = prcomp(data[,-1], retx=TRUE, center=TRUE,scale= TRUE)
str(Datax)
summary(Datax)
scores <- Datax$x
scores
sd <- Datax$sdev
loadings <- Datax$rotation
loadings[1:3,]
write.csv(loadings, "C:\\Users\\Desktop\\PCA\\pca.csv")
g <- ggbiplot(Datax,groups=Genotype,var.axes=FALSE,scale=1)
print(g)

Following is the picture of the PCA plot

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The picture isn't showing up. But more importantly, it doesn't seem like any of the code you're using involves Bioconductor packages (see A: Error in PCA analysis and with ggbiplot function for an answer to a related question). If I were you, I'd direct my queries towards the developer of ggbiplot.

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