[BioC] Different expression direction between limma microarray data analysis vs quantitative real time PCR result

Wang, Jixin jixinwang at tamu.edu
Tue Sep 22 01:50:19 CEST 2009

Hi, Chao-Jen,

Thanks for kind reply. I use limma for microarray data analysis. But for qRT-PCR, I first selected the optimal number of internal control genes by geNorm program, and then use those housekeeping genes that received best score for normalization of qRT-PCR. The qBasePlus software (Biogazelle, Belgium) was used to evaluate the relative gene expression across tissues and the statistical significance of the derived CNRQ values was determined by SPSS 17.0 statistics software. So I don’t think either microarray or real time analysis has problem. 

Best regards,


----- Original Message -----
From: "Chao-Jen Wong" <cwon2 at fhcrc.org>
To: jixinwang at tamu.edu
Cc: bioconductor at stat.math.ethz.ch
Sent: Monday, September 21, 2009 12:29:51 PM GMT -06:00 US/Canada Central
Subject: Re: [BioC] Different expression direction between limma microarray data analysis vs quantitative real time PCR result

Hi, Jixin,

Is your qRT-PCR expression level represented by cycle number (Ct) for
limma analysis? If it is, then one thing I can think of is that you need
to interpret the results in the opposite way. Since lower Ct means
higher expression level, the resulting negative t or B values indicate
up-regulation of the genes, not down-regulation.  If I am wrong, please
correct me.


jixinwang at tamu.edu wrote:
> Dear all,
> I use limma package to do microarray data analysis and most of real time PCR validation results are consistent with microarray data in terms of expression direction and statistical significance. However in one set of experiemnts, two DE genes are statistically significant in both of microarray and qRT-PCR result BUT had the different expression direction. (e.g. They are  down regulated in microarray result but real time PCR result showed that they are up regulated)? I don’t know why. Does this occur to anyone before? Many thanks.  
> Best regards,
> Wang
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

Chao-Jen Wong
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Avenue N., M2-B876
PO Box 19024
Seattle, WA 98109
cwon2 at fhcrc.org

More information about the Bioconductor mailing list