期刊
BIOINFORMATICS
卷 27, 期 6, 页码 764-770出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btr011
关键词
-
类别
资金
- National Science Foundation [EF-0849899, IIS-0812111, DMS-0616585]
- National Institutes of Health [1R21AI085376, 1R01HG0294501]
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [0812111] Funding Source: National Science Foundation
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据