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Zeng K, Fu YX, Shi S, Wu CI.. Statistical tests for detecting positive selection by utilizing high-frequency variants. Genetics 174: 1431-1439

State Key Laboratory of Biocontrol, Ministry of Education, Sun Yat-sen University, Guangzhou, China.
Genetics (Impact Factor: 4.87). 12/2006; 174(3):1431-9. DOI: 10.1534/genetics.106.061432
Source: PubMed

ABSTRACT By comparing the low-, intermediate-, and high-frequency parts of the frequency spectrum, we gain information on the evolutionary forces that influence the pattern of polymorphism in population samples. We emphasize the high-frequency variants on which positive selection and negative (background) selection exhibit different effects. We propose a new estimator of theta (the product of effective population size and neutral mutation rate), thetaL, which is sensitive to the changes in high-frequency variants. The new thetaL allows us to revise Fay and Wu's H-test by normalization. To complement the existing statistics (the H-test and Tajima's D-test), we propose a new test, E, which relies on the difference between thetaL and Watterson's thetaW. We show that this test is most powerful in detecting the recovery phase after the loss of genetic diversity, which includes the postselective sweep phase. The sensitivities of these tests to (or robustness against) background selection and demographic changes are also considered. Overall, D and H in combination can be most effective in detecting positive selection while being insensitive to other perturbations. We thus propose a joint test, referred to as the DH test. Simulations indicate that DH is indeed sensitive primarily to directional selection and no other driving forces.

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    • "Briefly, a large number of replicate simulations were performed for each demographic model, where the parameters of the model were drawn from prior distributions. Simulated data were summarized using h w (Watterson 1975), Tajima's D (Tajima 1989), the standardized Fay and Wu's H (Fay and Wu 2000; Zeng et al. 2006), and Kelly's Z nS (Kelly 1997) statistics. "
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    • "), Fay and Wu's H (Fay and Wu 2000), Zeng's E (Zeng et al. 2006), Strobeck's S (Strobeck 1987), Achaz's Y (Achaz 2009), Fu's F S (Fu 1997), Ramos-Onsins' and Rozas' R2 (Ramos-Onsins and Rozas 2002), as well as all corresponding theta values Linkage disequilibrium ZnS (Kelly 1997), B/Q (Wall 1999), ZA/ZZ (Rozas et al. 2001), and correlation coefficient r 2 for each pair of SNPs within or between windows/regions Recombination statistics Four-gamete test (Hudson and Kaplan 1985) Diversities Nucleotide and haplotype diversity (Hudson, Boos et al. 1992); (Nei 1979); see " Neutrality statistics " for a list of calculated Theta values Selective sweeps CL, CLR (Nielsen et al. 2005) FST estimates G ST (Nei 1973); F ST (Hudson, Slatkin et al. 1992); G ST , H ST , K ST (Hudson, Boos et al. 1992); S nn (Hudson 2000); Phi ST (Excoffier and Smouse 1992) MKT McDonald–Kreitman test (McDonald and Kreitman 1991) "
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    • "); D, Tajima's D statistic (Tajima 1989); D*, Fu and Li's D* test (Fu and Li 1993); H, Fay and Wu H test (Fay et al. 2002; Zeng et al. 2006); P(HKA), HKA test P value (Hudson et al. 1987). *P value 0.025 using three different demographic models (constant size, our best-fit model, and Hey 2010). "
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