Cutoff for coexpressed gene pairs using Pearson/Spearman correlation
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juls • 0
@juls-11275
Last seen 6 weeks ago
Austria

Dear all,

I am using the cor.test function (Spearman/Pearson correlation) to find coexpressed genes for a specific gene of interest in my microarray dataset (226 samples).

My question is now - what is the established cutoff for coexpression? Just the p-value results in a large number of coexpressed genes. I also categorised the genes according to correlation coefficient as in this list (see below), but is there any established cutoff > 0.5 or is indeed mainly the p-value used?
 

0-0.19 very weak
0.20-0.39 weak
0.40-0.59 moderate
0.60-0.79 strong
0.80-1.0 very strong

Thanks for advice!

Julia 

 

 

 
 

 

 

 

 

microarray pearsoncorrelation coexpression spearman • 1.0k views
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@james-w-macdonald-5106
Last seen 19 hours ago
United States

What about negative correlation? Is that not co-expression of a type as well?

Anyway, I am not sure inference will help you here, as a p-value doesn't measure the strength of correlation. Instead it just says how likely your result would be if the two genes really were not correlated. With 226 samples, even a pretty small correlation will have a p < 0.05 (somewhere around 0.11 or so). You will probably just have to set some ad hoc cutoff that you define as 'correlated enough' and go with that.

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Thanks for your answer.

I adjusted the p value, so it's around 0.18 but yes it's very low. Hence my question about an "established" cutoff. Any suggestions about a sensible cutoff here?
(The above list was also meant for negative correlation of course. I classified with the abs(correlation). I thought that was clear ;) - sorry)

 

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