I am an undergrad working on a set of genotype matrix of dogs, it's in csv file format with information on only the each sample as rows, chromosome and its position as columns, and the rest of the matrix is filled with 0,1,2 and missing values.

So I am wondering what would be the best method to impute the genotype with all the data I get? I looked up Impute2, but it seems to require the reference data(recombination map) which I don't have...

Really appreciate whoever answers my question!!

  • $\begingroup$ I have never inputted genotype data, but I am pretty sure a recombination map for dogs exists. Check for example here: ncbi.nlm.nih.gov/pmc/articles/PMC5100850 $\endgroup$ May 9, 2021 at 10:10
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    $\begingroup$ I've done imputation on dog data before - so I can hopefully help. However, I think we need some more information from you. How many individuals and SNPs do you have to begin with? Are the dogs the same breed or mixed? $\endgroup$
    – user438383
    May 9, 2021 at 15:52

1 Answer 1


Impute2 is a great, if dated choice. Another great choice is beagle. The advantage of beagle in this case is that it is not as strict about requiring a recombination map. Without a map, results will be poorer, but perhaps good enough.

Do make sure that your sample size including a reference panel is at least 200 in any case.


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