<p>Agreed with the above I would use an existing dataset from NCBIs dbSNP <a href="https://www.ncbi.nlm.nih.gov/snp/" rel="nofollow noreferrer">here</a></p>
<p>Random doesn't work well because HW signal will be meaningless as soon as the Jukes-Cantor distance is exceeded (which it will) and plink needs homologues to generate any signal either in 'reasonable' panmixia or clonality. The result will be panmictic beyond even the most panmictic organism ever known. I don't mind having a simulation of 100% clonalty, because 100% clonality does occur, either through inbreeding or binary division, but this simulation would generate the complete opposite result.</p>

CC BY-SA 4.0
2020-11-18T10:48:11.853Z
2020-11-18T10:48:11.853Z
M__
<p>I was wondering if there is a tool/script/program that randomly generates GWAS data. The purpose of such a tool would be to use it for educational purposes. So you generate some random .ped, .map and other filetypes. Various distributions like the MAF of all the SNPs, X-Chromosome classificaiton error rates and so on could be set before generating the data. General stuff one can then filter out with plink or similar software to increase the quality of the data.</p>
<p>Then a student would analyze these random files in plink and I already know what the outcome should be, therefore I can see right away if he or she did it right.</p>
<p>Does anyone know if such a program already exists? Or is there a somewhat easy way to program this myself?</p>
<p>Maybe it works if I use existing gene-data from NCBI where I use the given MAF to generate n variations the alleles based on that? Just some random SNPs from dbSNP?</p>

<snp><gwas><plink>
Random GWAS data generator
# Random GWAS data generator

(Asked by: username_0 on 2020-11-17)

I was wondering if there is a tool/script/program that randomly generates GWAS data. The purpose of such a tool would be to use it for educational purposes. So you generate some random .ped, .map and other filetypes. Various distributions like the MAF of all the SNPs, X-Chromosome classificaiton error rates and so on could be set before generating the data. General stuff one can then filter out with plink or similar software to increase the quality of the data.

Then a student would analyze these random files in plink and I already know what the outcome should be, therefore I can see right away if he or she did it right.

Does anyone know if such a program already exists? Or is there a somewhat easy way to program this myself?

Maybe it works if I use existing gene-data from NCBI where I use the given MAF to generate n variations the alleles based on that? Just some random SNPs from dbSNP?

**Tags:** snp, gwas, plink

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## 1 answers

### Answer by username_1 on 2020-11-18. Score: 1 | Accepted answer

Agreed with the above I would use an existing dataset from NCBIs dbSNP [here](https://www.ncbi.nlm.nih.gov/snp/)

Random doesn't work well because HW signal will be meaningless as soon as the Jukes-Cantor distance is exceeded (which it will) and plink needs homologues to generate any signal either in 'reasonable' panmixia or clonality. The result will be panmictic beyond even the most panmictic organism ever known. I don't mind having a simulation of 100% clonalty, because 100% clonality does occur, either through inbreeding or binary division, but this simulation would generate the complete opposite result.


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