An investigation of the statistical power of neutrality tests based on comparative and population genetic data
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An investigation of the statistical power of neutrality tests based on comparative and population genetic data. / Zhai, Weiwei; Nielsen, Rasmus; Slatkin, Montgomery.
In: Molecular Biology and Evolution, Vol. 26, No. 2, 2009, p. 273-83.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - An investigation of the statistical power of neutrality tests based on comparative and population genetic data
AU - Zhai, Weiwei
AU - Nielsen, Rasmus
AU - Slatkin, Montgomery
N1 - Keywords: Animals; Evolution, Molecular; Genetics, Population; Humans; Models, Statistical; Mutation; Pan troglodytes; Selection, Genetic
PY - 2009
Y1 - 2009
N2 - In this report, we investigate the statistical power of several tests of selective neutrality based on patterns of genetic diversity within and between species. The goal is to compare tests based solely on population genetic data with tests using comparative data or a combination of comparative and population genetic data. We show that in the presence of repeated selective sweeps on relatively neutral background, tests based on the d(N)/d(S) ratios in comparative data almost always have more power to detect selection than tests based on population genetic data, even if the overall level of divergence is low. Tests based solely on the distribution of allele frequencies or the site frequency spectrum, such as the Ewens-Watterson test or Tajima's D, have less power in detecting both positive and negative selection because of the transient nature of positive selection and the weak signal left by negative selection. The Hudson-Kreitman-Aguadé test is the most powerful test for detecting positive selection among the population genetic tests investigated, whereas McDonald-Kreitman test typically has more power to detect negative selection. We discuss our findings in the light of the discordant results obtained in several recently published genomic scans.
AB - In this report, we investigate the statistical power of several tests of selective neutrality based on patterns of genetic diversity within and between species. The goal is to compare tests based solely on population genetic data with tests using comparative data or a combination of comparative and population genetic data. We show that in the presence of repeated selective sweeps on relatively neutral background, tests based on the d(N)/d(S) ratios in comparative data almost always have more power to detect selection than tests based on population genetic data, even if the overall level of divergence is low. Tests based solely on the distribution of allele frequencies or the site frequency spectrum, such as the Ewens-Watterson test or Tajima's D, have less power in detecting both positive and negative selection because of the transient nature of positive selection and the weak signal left by negative selection. The Hudson-Kreitman-Aguadé test is the most powerful test for detecting positive selection among the population genetic tests investigated, whereas McDonald-Kreitman test typically has more power to detect negative selection. We discuss our findings in the light of the discordant results obtained in several recently published genomic scans.
U2 - 10.1093/molbev/msn231
DO - 10.1093/molbev/msn231
M3 - Journal article
C2 - 18922762
VL - 26
SP - 273
EP - 283
JO - Molecular Biology and Evolution
JF - Molecular Biology and Evolution
SN - 0737-4038
IS - 2
ER -
ID: 21332804