[BioC] Comparison of correlation coefficients

Christian.Stratowa at vie.boehringer-ingelheim.com Christian.Stratowa at vie.boehringer-ingelheim.com
Tue Jul 13 14:40:09 CEST 2004

Dear Bioconductor expeRts

Is it possible to compare correlation coefficients or to normalize 
different correlation coefficients?

Concretely, we have the following situation:
We have gene expression profiles for different tissues, where the 
number of samples per tissue are different, ranging from 10 to 250. 
We are able to determine the correlation between two genes A and B 
for each tissue separately, using "cor.test". However, the question 
arises if the correlation coefficients between different tissues can 
be compared or if they must somehow be "normalized", since the 
number of samples per tissue varyies. 

Searching the web I found the function "compcorr", see:
and implemented it in R:

compcorr <- function(n1, r1, n2, r2){
# compare two correlation coefficients
# return difference and p-value as list(diff, pval)

#	Fisher Z-transform
	zf1 <- 0.5*log((1 + r1)/(1 - r1))
	zf2 <- 0.5*log((1 + r2)/(1 - r2))

#	difference
	dz <- (zf1 - zf2)/sqrt(1/(n1 - 3) + (1/(n2 - 3)))

#	p-value
	pv <- 2*(1 - pnorm(abs(dz)))

	return(list(diff=dz, pval=pv))

Would it make sense to use the resultant p-value to "normalize" the 
correlation coefficients, using: corr <- corr * compcorr()$pval

Is there a better way or an alternative to "normalize" the correlation 
coefficients obtained for different tissues?

Thank you in advance for your help.
Since in the company I am not subscribed to bioconductor-help, could you 
please reply to me (in addition to bioconductor-help)

P.S.: I have posted this first at r-help and it was suggested to me to 
post it here, too.

Best regards
Christian Stratowa

Christian Stratowa, PhD
Boehringer Ingelheim Austria
Dept NCE Lead Discovery - Bioinformatics
Dr. Boehringergasse 5-11
A-1121 Vienna, Austria
Tel.: ++43-1-80105-2470
Fax: ++43-1-80105-2782
email: christian.stratowa at vie.boehringer-ingelheim.com

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