Khan Zia, Bloom Joshua S, Kruglyak Leonid, Singh Mona
Department of Computer Science, Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
Bioinformatics. 2009 Jul 1;25(13):1609-16. doi: 10.1093/bioinformatics/btp275. Epub 2009 Apr 23.
High-throughput sequencing technologies place ever increasing demands on existing algorithms for sequence analysis. Algorithms for computing maximal exact matches (MEMs) between sequences appear in two contexts where high-throughput sequencing will vastly increase the volume of sequence data: (i) seeding alignments of high-throughput reads for genome assembly and (ii) designating anchor points for genome-genome comparisons.
We introduce a new algorithm for finding MEMs. The algorithm leverages a sparse suffix array (SA), a text index that stores every K-th position of the text. In contrast to a full text index that stores every position of the text, a sparse SA occupies much less memory. Even though we use a sparse index, the output of our algorithm is the same as a full text index algorithm as long as the space between the indexed suffixes is not greater than a minimum length of a MEM. By relying on partial matches and additional text scanning between indexed positions, the algorithm trades memory for extra computation. The reduced memory usage makes it possible to determine MEMs between significantly longer sequences.
Source code for the algorithm is available under a BSD open source license at http://compbio.cs.princeton.edu/mems. The implementation can serve as a drop-in replacement for the MEMs algorithm in MUMmer 3.
高通量测序技术对现有的序列分析算法提出了越来越高的要求。用于计算序列之间最大精确匹配（MEM）的算法出现在两个场景中，高通量测序将极大地增加序列数据量：（i）为基因组组装对高通量读段进行比对的种子设定，以及（ii）为基因组-基因组比较指定锚定位置。
我们引入了一种用于查找MEM的新算法。该算法利用了稀疏后缀数组（SA），这是一种存储文本中每隔K个位置的文本索引。与存储文本每个位置的全文本索引相比，稀疏SA占用的内存要少得多。即使我们使用的是稀疏索引，只要索引后缀之间的间距不大于MEM的最小长度，我们算法的输出就与全文本索引算法相同。通过依赖部分匹配以及在索引位置之间进行额外的文本扫描，该算法用内存换取了额外的计算量。减少的内存使用使得确定显著更长序列之间的MEM成为可能。
该算法的源代码可在http://compbio.cs.princeton.edu/mems以BSD开源许可获取。该实现可以作为MUMmer 3中MEM算法的直接替代品。
