Fst in tskit (equivalent to Reynolds et al 1983) #2341
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Does anybody know if the Fst implemented in tskit is formally equivalent to the coefficient of coancestry derived in Reynolds et al 1983 (theta on pg 769, Genetics 105:767-779)? There are different ways of estimating Fst, but when I collect the various x1,x2,n1,n2 terms in
(see summary functions at the end of https://github.com/tskit-dev/tskit/discussions/new ), I don't quite get the Reynolds et al expression. I don't know if something went wrong with my algebra or if the estimates are in fact not equivalent. |
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Replies: 2 comments 3 replies
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I think it is not formally equivalent, even for the biallelic case, as Reynolds et al is defining things in terms of variance components (that's what |
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Unfortunately, we will probably need to run Reynolds Fst in order to
compare the output of demographic models to our data for consistency. If I
have a python script def rey_fst(freq1, freq2, SampleSize1, SampleSize2)
that calculates Reynolds Fst at each segregating site given allele
frequency and sample size for samples 1,2, what is the most efficient way
to extract this information from a ts object to get window Reynolds Fst?
…On Wed, Jun 15, 2022 at 3:11 PM Peter Ralph ***@***.***> wrote:
I *think* it is not formally equivalent, even for the biallelic case, as
Reynolds et al is defining things in terms of variance components (that's
what a and b are), and our definition is in terms of probabilities of
idenity, but I'd have to do a fair bit of math to check. We certainly
*could* add the Reynolds estimator as an option (e.g., ts.Fst(...,
method="reynolds"), but for genomic data (ie, lots of mostly biallelic
snps) the difference is negligible (at least in cases where I've done that
check).
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Max Shpak, Ph.D.
Department of Genetics
University of Wisconsin
Madison, WI 53706
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I think it is not formally equivalent, even for the biallelic case, as Reynolds et al is defining things in terms of variance components (that's what
a
andb
are), and our definition is in terms of probabilities of idenity, but I'd have to do a fair bit of math to check. We certainly could add the Reynolds estimator as an option (e.g.,ts.Fst(..., method="reynolds")
, but for genomic data (ie, lots of mostly biallelic snps) the difference is negligible (at least in cases where I've done that check).