Cutoff for coexpressed gene pairs using Pearson/Spearman correlation
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juls • 0
Last seen 9 months ago

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!









microarray pearsoncorrelation coexpression spearman • 1.2k views
Entering edit mode
Last seen 2 days 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.

Entering edit mode

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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