基于局部敏感哈希的系统发育树快速构建
Fast reconstruction of phylogenetic trees using locality-sensitive hashing
摘要：
我们提出了第一次二次时间算法，具有高概率正确重建系统发育树的马尔可夫模型的演变产生的短序列。由于序列数据库的快速扩展，这种非常快速的算法变得必要。已经开发了其他快速算法用于从非常大的比对构建树（Price等人和Brown等人），但是它们缺乏理论性能保证。我们的新算法运行在$O(n^{1+γ(g)}\log^2n)$时间，其中$γ$是一个递增的函数的上界上的分支长度的遗传，上界$g$必须低于$1/2-\sqrt{1/8} \approx 0.15$，和$γ(g)<1$的所有$g$。对于分支很短的分支，我们的算法的运行时间接近线性。例如，如果所有分支长度对应于小于0.02的突变概率，则我们的算法的运行时间大致为$O(n^{1.2}\log^2n)$。通过一个原型和一系列的大规模实验，我们表明，许多大的megenies可以快速重建，而不影响重建精度。
英文摘要：
We present the first sub-quadratic time algorithm that with high probability correctly reconstructs phylogenetic trees for short sequences generated by a Markov model of evolution. Due to rapid expansion in sequence databases, such very fast algorithms are becoming necessary. Other fast heuristics have been developed for building trees from very large alignments (Price et al, and Brown et al), but they lack theoretical performance guarantees. Our new algorithm runs in $O(n^{1+γ(g)}\log^2n)$ time, where $γ$ is an increasing function of an upper bound on the branch lengths in the phylogeny, the upper bound $g$ must be below$1/2-\sqrt{1/8} \approx 0.15$, and $γ(g)<1$ for all $g$. For phylogenies with very short branches, the running time of our algorithm is close to linear. For example, if all branch lengths correspond to a mutation probability of less than 0.02, the running time of our algorithm is roughly $O(n^{1.2}\log^2n)$. Via a prototype and a sequence of large-scale experiments, we show that many large phylogenies can be reconstructed fast, without compromising reconstruction accuracy.
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