Applied Mathematics Program, Yale University, 51 Prospect St., New Haven, CT 06511, USA.
BMC Bioinformatics. 2013;14 Suppl 5(Suppl 5):S8. doi: 10.1186/1471-2105-14-S5-S8. Epub 2013 Apr 10.
Read alignment is a computational bottleneck in some sequencing projects. Most of the existing software packages for read alignment are based on two algorithmic approaches: prefix-trees and hash-tables. We propose a new approach to read alignment using random permutations of strings.
We present a prototype implementation and experiments performed with simulated and real reads of human DNA. Our experiments indicate that this permutations-based prototype is several times faster than comparable programs for fast read alignment and that it aligns more reads correctly.
This approach may lead to improved speed, sensitivity, and accuracy in read alignment. The algorithm can also be used for specialized alignment applications and it can be extended to other related problems, such as assembly.More information: http://alignment.commons.yale.edu.
在某些测序项目中,读取比对是一个计算瓶颈。大多数现有的读取比对软件包都基于两种算法方法:前缀树和哈希表。我们提出了一种使用字符串随机排列进行读取比对的新方法。
我们提出了一个原型实现,并使用人类 DNA 的模拟和真实读取进行了实验。我们的实验表明,这种基于排列的原型比用于快速读取比对的可比程序快几倍,并且它可以正确对齐更多的读取。
这种方法可能会提高读取比对的速度、灵敏度和准确性。该算法还可用于专门的对齐应用程序,并且可以扩展到其他相关问题,例如组装。更多信息:http://alignment.commons.yale.edu。