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A fast, lock-free approach for efficient parallel counting of occurrences of k-mers.

机译:一种快速,无锁的方法,可有效地并行计算k-mers的出现。

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MOTIVATION: Counting the number of occurrences of every k-mer (substring of length k) in a long string is a central subproblem in many applications, including genome assembly, error correction of sequencing reads, fast multiple sequence alignment and repeat detection. Recently, the deep sequence coverage generated by next-generation sequencing technologies has caused the amount of sequence to be processed during a genome project to grow rapidly, and has rendered current k-mer counting tools too slow and memory intensive. At the same time, large multicore computers have become commonplace in research facilities allowing for a new parallel computational paradigm. RESULTS: We propose a new k-mer counting algorithm and associated implementation, called Jellyfish, which is fast and memory efficient. It is based on a multithreaded, lock-free hash table optimized for counting k-mers up to 31 bases in length. Due to their flexibility, suffix arrays have been the data structure of choice for solving many string problems. For the task of k-mer counting, important in many biological applications, Jellyfish offers a much faster and more memory-efficient solution. AVAILABILITY: The Jellyfish software is written in C++ and is GPL licensed. It is available for download at http://www.cbcb.umd.edu/software/jellyfish.
机译:动机:计算长字符串中每个k-mer(长度为k的子字符串)出现的次数是许多应用中的中心子问题,包括基因组组装,测序读数的错误校正,快速多序列比对和重复检测。近来,下一代测序技术所产生的深层序列覆盖已导致在基因组计划期间要处理的序列数量迅速增长,并使当前的k-mer计数工具太慢且占用大量内存。同时,大型多核计算机在研究机构中变得司空见惯,从而允许一种新的并行计算范式。结果:我们提出了一种新的k-mer计数算法及相关的实现,称为水母,该算法快速且存储效率高。它基于多线程,无锁哈希表,该哈希表经过优化,可计算最多31个碱基的k-mers。由于其灵活性,后缀数组已成为解决许多字符串问题的首选数据结构。对于k-mer计数的任务(在许多生物学应用中很重要),水母提供了更快,更高效的存储解决方案。可用性:水母软件是用C ++编写的,并且已获得GPL许可。可从http://www.cbcb.umd.edu/software/jellyfish下载。

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