Kahveci Tamer, Ljosa Vebjorn, Singh Ambuj K
Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA 93106-5110, USA.
Bioinformatics. 2004 Sep 1;20(13):2122-34. doi: 10.1093/bioinformatics/bth212. Epub 2004 Apr 8.
Many biological applications require the comparison of large genome strings. Current techniques suffer from high computational and I/O costs.
We propose an efficient technique for local alignment of large genome strings. A space-efficient index is computed for one string, and the second string is compared with this index in order to prune substring pairs that do not contain similar regions. The remaining substring pairs are handed to a hash-table-based tool, such as BLAST, for alignment. A dynamic strategy is employed to optimize the number of disk seeks needed to access the hash table. Additionally, our technique provides the user with a coarse-grained visualization of the similarity pattern, quickly and before the actual search. The experimental results show that our technique aligns genome strings up to two orders of magnitude faster than BLAST. Our technique can be used to accelerate other search tools as well.
A web-based demo can be found at http://bioserver.cs.ucsb.edu/. Source code is available from the authors on request.
许多生物学应用需要对大型基因组字符串进行比较。当前技术存在高计算成本和高I/O成本的问题。
我们提出了一种用于大型基因组字符串局部比对的高效技术。为一个字符串计算一个节省空间的索引,将第二个字符串与该索引进行比较,以修剪不包含相似区域的子串对。其余的子串对交给基于哈希表的工具(如BLAST)进行比对。采用动态策略来优化访问哈希表所需的磁盘寻道次数。此外,我们的技术在实际搜索之前快速为用户提供相似性模式的粗粒度可视化。实验结果表明,我们的技术比对基因组字符串的速度比BLAST快两个数量级。我们的技术也可用于加速其他搜索工具。