Evolutionary Dynamics and Biophysics Group, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.
Bioinformatics. 2012 Dec 15;28(24):3332-3. doi: 10.1093/bioinformatics/bts633. Epub 2012 Oct 24.
The analysis of the evolutionary dynamics of a population with many polymorphic loci is challenging, as a large number of possible genotypes needs to be tracked. In the absence of analytical solutions, forward computer simulations are an important tool in multi-locus population genetics. The run time of standard algorithms to simulate sexual populations increases as 8(L) with the number of loci L, or with the square of the population size N.
We have developed algorithms to simulate large populations with arbitrary genetic maps, including multiple crossovers, with a run time that scales as 3(L). If the number of crossovers is restricted to at most one, the run time is reduced to L2(L). The algorithm is based on an analogue of the Fast Fourier Transform (FFT) and allows for arbitrary fitness functions (i.e. any epistasis). In addition, we include a streamlined individual-based framework. The library is implemented as a collection of C++ classes and a Python interface.
分析具有许多多态性基因座的群体的进化动态具有挑战性,因为需要跟踪大量可能的基因型。在没有分析解决方案的情况下,正向计算机模拟是多基因座群体遗传学的重要工具。模拟有性群体的标准算法的运行时间随基因座数 L 或种群大小 N 的平方呈 8(L) 增加。
我们已经开发了算法来模拟具有任意遗传图谱的大型种群,包括多个交叉点,运行时间为 3(L)。如果将交叉点的数量限制在最多一个,则运行时间减少到 L2(L)。该算法基于快速傅里叶变换(FFT)的模拟,并允许任意适应度函数(即任何上位性)。此外,我们还包括了一个简化的基于个体的框架。该库实现为 C++类的集合和 Python 接口。