Guys,
I tried to compare two vectors and each vector is a RPKM value I calculated using ChIP-seq reads. I want to use pearson correlation as a way to access the similarity between two ChIP-seq datasets.
The two RPKM values are values in 500bp bins genome-wide, for mouse. So there are more than 5 million bins in total. I checked the difference between two RPKM value files and they are actually very similar. So presumably the pearson correlation coefficient should be very close to 1.
However, when I used cor.test() in R, the output is like this:
I couldn't figure out why I got a weird correlation like that.. does anyone have an idea of why it's the case? Did I do something completely wrong?
Thanks a lot!
I tried to compare two vectors and each vector is a RPKM value I calculated using ChIP-seq reads. I want to use pearson correlation as a way to access the similarity between two ChIP-seq datasets.
The two RPKM values are values in 500bp bins genome-wide, for mouse. So there are more than 5 million bins in total. I checked the difference between two RPKM value files and they are actually very similar. So presumably the pearson correlation coefficient should be very close to 1.
However, when I used cor.test() in R, the output is like this:
Pearson's product-moment correlation
data: a$V4 and b$V4
t = -0.0037, df = 5309833, p-value = 0.9971
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.0008521632 0.0008489671
sample estimates:
cor
-1.598034e-06
data: a$V4 and b$V4
t = -0.0037, df = 5309833, p-value = 0.9971
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.0008521632 0.0008489671
sample estimates:
cor
-1.598034e-06
Thanks a lot!
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