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On the Meaning of Averages in Genome-wide Association Studies: What Should Come Next?

Rauch, Cyril; Wattis, Jonathan; Bray, Sian


Associate Professor

Professor of Applied Mathematics

Assistant Professor in Bioinformatics


Identifying the association between phenotypes and genotypes is the fundamental basis of genetic analyses. Although genomic technologies used to generate data have rapidly advanced within the last 20 years, the statistical models used in genome-wide associations studies (GWAS) to analyse the data are still predominantly based on the model developed by Fisher more than 100 years ago. The question is, does Fisher’s theory need to be replaced or improved, and if so, what should come next? The theory developed by Fisher was inspired by the field of probability. To make use of probability not only did Fisher have to assume valid a number of questionable hypotheses, but he also had to conceptually frame genotypephenotype associations in a specific way giving primordial importance to the notion of average. However, the ‘average’ in probability results from the notions of ‘imprecision’ or ‘ignorance’. After reviewing the historical emergence and societal impact of probability as a method, it is clear what is needed now is a new method acknowledging precision in measurements. That is, a method that does not rely on categorizing or binning data.


Rauch, C., Wattis, J., & Bray, S. (2023). On the Meaning of Averages in Genome-wide Association Studies: What Should Come Next?. Organisms, 6(1), 7-22.

Journal Article Type Article
Acceptance Date Oct 3, 2022
Online Publication Date Jan 17, 2023
Publication Date Jan 17, 2023
Deposit Date Oct 11, 2022
Publicly Available Date Oct 11, 2022
Peer Reviewed Peer Reviewed
Volume 6
Issue 1
Pages 7-22
Public URL
Publisher URL


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