geNorm is a popular algorithm to determine the most stable reference (housekeeping) genes from a set of tested candidate reference genes in a given sample panel. From this, a gene expression normalization factor can be calculated for each sample based on the geometric mean of a user-defined number of reference genes.

The Microsoft Excel geNorm version from 2002 has been downloaded more than 15,000 times worldwide. Since 2010, a much improved geNorm module is integrated in the qbase+ software (both basic and premium license) for real-time PCR data analysis in Windows, Mac and Linux (available from Biogazelle). The manual is available here.

The underlying principles and formulas are described in Vandesompele et al., Genome Biology, 2002, 'Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes'. The full article can be read at http://genomebiology.biomedcentral.com/articles/10.1186/gb-2002-3-7-research0034
[nr 13 in ranking of all time most-viewed articles published by BioMed Central]

In a follow-up paper we developed the global mean normalization method (also available in qbase+) that is especially useful for normalization of data coming from a large and unbiased set of genes, e.g. microRNA gene expression profiling: Mestdagh et al., Genome Biology, 2009, 'A novel and universal method for microRNA RT-qPCR data normalization'. The full article can be read at http://genomebiology.com/2009/10/6/R64

[geNorm citations]

According to Google Scholar, more than 11,000 papers have cited the geNorm method.

[Improved geNorm in qbase+ software]

The old geNorm for Microsoft Excel is no longer available for several reasons (no longer compatible since several versions of Excel, slow, buggy, difficult to use).

The benefits of the new module in qbase+ are:
- fully automatic and expert result report
- handles missing data
- single best reference gene identification
- available for Windows, Mac and Linux
- much faster
The manual is available here (requires free login to the MyBiogazelle community).

[How to get geNorm?]

geNorm is part of Biogazelle's qbase+ software for real-time PCR data-analysis and is available for 299 EUR.

1. Download and install the qbase+ software in your qbase+ account
2. Evaluate 15-days demonstration software or purchase qbase+ license

[discussion group]

An accompanying (but discontinued) discussion group to foster discussions between geNorm users so that they can share experiences and solutions doing gene expression normalization can be found at http://groups.yahoo.com/group/genorm. While this group is closed for new entries, the questions and answers are still available.

[geNorm detection kits]

geNorm based reference gene quantification kits are available commercially from PrimerDesign Ltd. Currently available are primer sets to detect a wide variety of Homo, Mus, Rattus, Caenorhabditis, Xenopus, Arabidopsis and Ovis normalising genes.
Kits purchased from PrimerDesign come with a premium qbase+ licence to use the geNorm software in conjunction with the kit.


"We have been using geNorm when examining cell wall synthesis enzymes in barley tissues and are happy with the results. Thanks for generating such a useful tool and making it universally available."
Neil Shirley, University of Adelaide, Australia

"I am extremely impressed with this approach to normalization."
Chris Tse, Sagres Discovery, USA

"I can no longer analyze my PCR runs without using geNorm!"
Marie-Jeanne Pillaire, CNRS, France

[reference gene primer sequences]

Primer sequences for many reference genes are available in the real-time PCR primer and probe database RTPrimerDB.
You are kindly invited to submit your validated primer (and probe) sequences to RTPrimerDB, so that other users can benefit from your expertise.
The database is available at http://www.rtprimerdb.org, and was first described in Pattyn et al., RTPrimerDB: the Real-Time PCR primer and probe database. Nucleic Acids Research, 2003, 31(1): 122-123 (full text)
For new RT-qPCR assay designs, we invite you to try primerXL at primerXL.

last update on 2017-04-07