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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