Genomic scans for selective sweeps using SNP data
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Genomic scans for selective sweeps using SNP data. / Nielsen, Rasmus; Williamson, Scott; Kim, Yuseob; Hubisz, Melissa J.; Clark, Andrew G.; Bustamente, Carlos.
In: Genome Research, Vol. 15, No. 11, 2005, p. 1566-1575.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Genomic scans for selective sweeps using SNP data
AU - Nielsen, Rasmus
AU - Williamson, Scott
AU - Kim, Yuseob
AU - Hubisz, Melissa J.
AU - Clark, Andrew G.
AU - Bustamente, Carlos
PY - 2005
Y1 - 2005
N2 - Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.
AB - Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.
U2 - 10.1101/gr.4252305
DO - 10.1101/gr.4252305
M3 - Journal article
C2 - 16251466
VL - 15
SP - 1566
EP - 1575
JO - Genome Research
JF - Genome Research
SN - 1088-9051
IS - 11
ER -
ID: 87169