I was having this issue too. I think you're correct. I assume that popGenome is breaking each individual into two due to the ploidy level. If you specify the argument diploid = TRUE, it will add the duplicates together.
Hi,
I'm trying to use the package PopGenome but I'm running into a problem where all of my indivduals appear to be duplicated. When I use get.individuals like they did in the answer here: Defining populations in PopGenome after running readMS instead of getting (for example) "1", "2","3", etc, I'm getting "1", "1.2", "2", "2.2", "3", "3.2", etc. I have no idea why it's doing this and I've looked all through the documents I can find to try figure it out, but I just can't! I also had the exact same problem when I used the example data provided here (https://github.com/tonig-evo/workshop-popgenome/tree/master), so it doesn't appear to be a problem with my data.
My code so far is simply:
Genome <- readData("VCF", format="VCF")
get.individuals(Genome)
Any help would be appreciated!
1 answer
Hi! I stumbled upon this post because I also thought something was wrong. Setting diploid to true leads to the duplicated samples, when I am using the set.populations function. Is it possible that the methods you are using have defaulted to diploid?
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Hi, I am facing the same problem and wondering if you have found solution to this problem?