Slicing and Dicing the Genome: A Statistical Physics Approach to Population Genetics

被引:1
|
作者
Maruvka, Yosef E. [1 ]
Shnerb, Nadav M. [1 ]
Solomon, Sorin [2 ]
Yaari, Gur [3 ]
Kessler, David A. [1 ]
机构
[1] Bar Ilan Univ, Dept Phys, IL-52900 Ramat Gan, Israel
[2] Hebrew Univ Jerusalem, Racah Inst Phys, IL-91904 Jerusalem, Israel
[3] Yale Univ, Dept Ecol & Evolutionary Biol, New Haven, CT 06520 USA
关键词
Galton-Watson theory; Haplotype statistics; Population genetics; MAXIMUM-LIKELIHOOD-ESTIMATION; SUBSTITUTION RATE VARIATION; ANCESTRAL INFERENCE; MITOCHONDRIAL-DNA; SAMPLING THEORY; RATES; COMPUTATION; SEQUENCES; TREES; SITES;
D O I
10.1007/s10955-010-0113-7
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The inference of past demographic parameters from current genetic polymorphism is a fundamental problem in population genetics. The standard techniques utilize a reconstruction of the gene-genealogy, a cumbersome process that may be applied only to small numbers of sequences. We present a method that compares the total number of haplotypes (distinct sequences) with the model prediction. By chopping the DNA sequence into pieces we condense the immense information hidden in sequence space into a function for the number of haplotypes versus subsequence size. The details of this curve are robust to statistical fluctuations and are seen to reflect the process parameters. This procedure allows for a clear visualization of the quality of the fit and, crucially, the numerical complexity grows only linearly with the number of sequences. Our procedure is tested against both simulated data as well as empirical mtDNA data from China and provides excellent fits in both cases.
引用
收藏
页码:1302 / 1316
页数:15
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