I am investigating on SNP-trait association in a species with a narrow genetic base. I have phenotyped and genotyped 80 accessions. I would like to use GWAS for the association analysis.
From literature, a suitable GWAS analysis requires a large sample size. My question is: what is the minimum sample size required for GWAS? Or How large should the sample size be?
All depends on the statistical power you want to reach and the relatedness of your OTUs. There is clear relationship between the effective sample size and the statistical power of your association study. But you can read more here doi: 10.5808/GI.2012.10.2.117 and also here doi: https://doi.org/10.1101/2019.12.15.877217
Thank you very much Professor Achigan-Dako for your answer and resources sharing.
It is true that a large and representative sample increases the power of detecting QTLs and the map resolution. The decision about actual sample size in GWAs is driven by a number of considerations including the nature of the trait of interest, the actual diversity of the species, the available resources for effective phenotyping (very critical aspect) and genotyping etc....
The following paper shed some lights on the question. Article The Advantages and Limitations of Trait Analysis With Gwas: A Review
Yes, sample size affects power. The diversity and structure of you population also matter. 80 accessions are okay if they fairly represent the genetic breadth of the target pool.
It is better to use more than 100 individuals (>300 is prefer) to perform GWAS. Restricted population size will significantly lower the power and increase false positive. Theoretical and applied genetics will not consider GWAS with population size less than 100.
Hi
Although it is theoretically proved that the larger the sample size, the better result, but we know that in reality, this will not always be possible.
Virtually every study requires a number of issues to be considered for determination of the minimum sample size:
1- The species under study due to the LD and LD pattern, the fundamental need for the association tests.
2- The power desired
3- The desired level of significance
4- Minner allele frequency in the studied population
5- The nature of the interesting trait
6- Type of study, for example, case-control, family-based or population-based
7- Population structure
8- Existence of confounding factors
There are also online calculating tools for determining sample size like OSSE.
Of course, I haven't used it and I don't know how helpful it can be. But can be tested.
Best regards
True, the larger the population, the better the GWAS, but sometimes we just have to do with what we have. No matter your population size (select a descent journal that can accept such population), try to focus on effectively controlling false positives and negatives through a optimization of your analyses. Using R to run GWAS is very helpful since you can adapt scripts to optimize the control of population parameters while checking what the QQ-plot looks like. Find a better explanation here: https://www.mdpi.com/2073-4425/11/6/689.
Kindly refer to this article for further information on the matter at hand. Article Sample Size for Successful Genome-Wide Association Study of ...
I am working on bacterial gwas and have the same question, while reading paper today, and want to share what I read"Sample size, unlike in human GWAS, mostly poses a subtle problem as most variants in microbial genomes are under strong selection and therefore present large effect sizes even with small datasets"
---Article Current Affairs of Microbial Genome-Wide Association Studies...
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