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I think I have seen that also.

There is easy way how to avoid this. You have to filter the samples being merged to the large dataset to only those SNPs already existing in the large dataset, else the extraneous SNPs in the sample that don't occur in the large forces the large to add No Calls to every sample in it swelling...

There was a recent publication claming similar not too far ago.. So this ChatCPT creation is a good example of Google Search . You posted this in another topic as well. Next time when you use ChatGPT do also your own search with Google or other search engines to see who is the original source...

What is the question ? You did not share your own results on G25 and I don't see what is your good fit. Regarding G25 the best place to ask is Davidsky at his blog Eurogenes.

This is not a good idea to use *.ped as extention for the parameter file. You may use .txt or .par instead. .ped is used for packed eisenstrat file format.. Just try to avoid that kind of mess. In the original software from git hub or downlowad there are excelent examples for parameter files...

Actually - you don`t need that much 100GB for the conversion. But you need lot of RAM on you computer. The conversion may take some time, may be half an hour or more. On slow computer it may not run at all or may freeze.The result from geno to ped will generate the same size file , near 5 GB...

Yes, both convertions are possible. The templates for parameter files are provided with Eigensoft: https://github.com/argriffing/eigensoft/tree/master/CONVERTF echo " genotypename: full230.geno snpname: full230.snp indivname: full230.ind outputformat: PACKEDPED genotypeoutname: full230.bed...

plink is available for both Linux ana Windows OS. However the question was for convertf. So convertf is Linux only. There are also other tools to convert from one format to another, but convertf is the easiest ways.

The only way to do it is from Linux , I don't think think there is Windows version, at least I don't use it. I use Ubuntu VM for the conversion. The command is convertf -p parameters_file In parameters_file you specify the filenames that should be converted and the output file names. In...

yes, I do it .

I checked who is the most similar to Etruscans and I compared with some new samples from KapitanAndreevo from the latest dataset. I can say these are almost between the Etruscans. Here is the list of the individuals to verify: TAQ001 TAQ024 TAQ017 TAQ005 TAQ015 TAQ018...

The easiest way - you take a screenshot or save the results as png or pdf file. However you may save it in another file - for example text file. I created my own scripts to save such data. I can share, but it's not perfect. It just work for me. To save: # Find the best result min_score <-...

Actually: it is the Pop3 in the focus. We test if Pop3 is in the middle between pop1/pop2 or how far is pop3 on one side or another. This is good to know: F3(A,B,C) = F4(A,B, A,C) https://uqrmaie1.github.io/admixtools/reference/qp3pop.html In the description of the function they generaly...

Some instructions and examples are available here: https://uqrmaie1.github.io/admixtools/articles/admixtools.html

They can use it both way: 1. To test if c is in the middle between a,b. 2. To test how far is c from a and b. F3=<(c-a)(c-b)>

p - the probability if there is a connection/ relation between pop2 and pop1 / pop3 se- standard error est - The estimated F3-statistics In your case here, there is no relation between pop2 and 2 others. The probability = 0. Z is too big and positive. If they were related - Z would be near 0...

Hello guys, We have the latest data available for SouthernArc publications. The Zipped data has 5940 individuals, both previously known and new. The new data is for 778 individuals. Because of missing data, I had to do the full quality control on the provided data: plink --memory 12000...

The best part of admixtools2 for me is F3 /F4 statistics. Especially F3. I tested some other functions, but don't seems to be much useful for me. qpgraph / QPWave is great too.. However depending on the selection of individuals / populations the results from QPwave could vary too much.

Genetic distance is calculated as a product / multiplication/ of multidimentional vectors. When the 2 vectors are perpendicular, their scalar product =0. If we take the 2 dimentional space - it will be a circle, all the dots in this cercle will have 0 distance. In 3D - it wiil be a...