Hello, I'm trying to find consensus modules between 2 gene co-expression networks. But the sample size used to construct networks are different. Is there a way to adjust correlation based on sample size? Thanks in advance.

Hamid

Is there a way to adjust correlation based on sample size

1

Entering edit mode

8.7 years ago

beiki.h.m
▴
10

Hello, I'm trying to find consensus modules between 2 gene co-expression networks. But the sample size used to construct networks are different. Is there a way to adjust correlation based on sample size? Thanks in advance.

Hamid

0

Entering edit mode

8.7 years ago

Michael
54k

If you use a correlation test to generate your co-expression network, the test statistics and thereby a p-value will depend on the degrees of freedom, and thereby be corrected for sample size, such that the same correlation of two larger vectors is more significant than that of a shorter one (resembling your intuition). You might then -in addition- want to correct the p-values for multiple testing.

See for example cor.test in R:

https://stat.ethz.ch/R-manual/R-devel/library/stats/html/cor.test.html

Example:

```
> x = c(1,1.1,1) ; y = c(1,1.5,1.2)
> cor.test (c(x),c(y))
Pearson's product-moment correlation
data: c(x) and c(y)
t = 2.3094, df = 1, p-value = 0.2601
alternative hypothesis: true correlation is not equal to 0
sample estimates:
cor
0.9176629
> cor.test (c(x,x),c(y,y))
Pearson's product-moment correlation
data: c(x, x) and c(y, y)
t = 4.6188, df = 4, p-value = 0.00989
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.4156606 0.9911073
sample estimates:
cor
0.9176629
```

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Dear Michael

Thanks to your response. Actually I don't want to apply a threshold for correlations. I want to use WGCNA procedure to construct my networks. In short, it reach each correlation to a power of "k" to make them smaller and then apply clustering method to construct the network. So, because I have different networks and I want to compare them, I should adjust correlations in each network based on the sample size that used for its construction.

Thanks

have you solved the problem yet? I've been troubled by the same problem and looking forward to a solution.

@Michael Dondrup what if I have two correlational networks (from two experimental conditions) one of size 8 samples and one is of size 32 samples. How I can make these two compare with each other or how to readjust correlation or calculate p-adjust with respect to the different number of samples. I used psych tool to calculate Padjusted value, but it uses the t-test, is n't it biased for the small number of samples?