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Publications (4)
Bolivian Creole cattle populations evolved under low levels of breeding management and, during more than 500 years of natural selection, became adapted to various environments such as the contrasting highland and subtropical environments. Recently, highland Creole cattle were crossbred with Holstein to improve dairy production. The aim of this rese...
Brangus is a composite cattle breed developed with the objective of combining the advantages of Angus and Zebuine breeds (Brahman, mainly) in tropical climates. The aim of this work was to estimate breed composition both genome‐wide and locally, at the chromosome level, and to uncover genomic regions evidencing positive selection in the Argentinean...
Over 65% of the world's cattle population resides in warm areas where heat stress conditions limit the breed of European taurine cattle. Composite breeds were developed to retain the main traits of both parental breeds. The skin plays a central role in animal response to heat stress. Research on the genetic architecture of skin traits has identifie...
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Question (1)
Hi!
I calculated Fst values from a 40K SNPs dataset, with plink2 (https://www.cog-genomics.org/plink/2.0/), using --fst function. The output are raw values and I was reseaching about how people deal with the statistic part.
My main question is, which is the best way to estimate p-values from this raw Fst values?
Thanks in advanced.