基于Burrows-Wheeler变换的LCP阵列空间高效计算

N. Prezza, Giovanna Rosone
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引用次数: 9

摘要

我们证明了总大小为n的字母[1,{\sigma}]的文本集合的最长公共前缀数组可以在O(n log {\sigma})时间内从Burrows-Wheeler变换集合中计算出来,使用O(n log {\sigma})位的工作空间在输入和输出之上。我们的结果改进了(在小字母上)并推广了(在字符串集合上)先前由Beller等人提出的解决方案,后者需要O(n)位的额外工作空间。我们还展示了如何在相同的时间和空间范围内合并总大小为n的两个集合的bwt。我们算法的核心过程可以用来从BWT中枚举简洁空间中的后缀树区间,这是一个独立的兴趣。我们在DNA字母表上的第一个算法的工程实现诱导了一个大型(16 GiB)短(100个碱基)读取集合的LCP,速率为2.92兆碱基/秒,每个碱基在RAM中总共使用1.5字节。我们的第二个算法以每秒1.7兆字节的速率合并两个8 GiB的短读集合的bwt,并且在RAM中每个基使用0.625字节。该算法的扩展还计算合并集合的LCP数组,以每秒1.48兆基的速率处理数据,并在RAM中使用每个基1.625字节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Space-Efficient Computation of the LCP Array from the Burrows-Wheeler Transform
We show that the Longest Common Prefix Array of a text collection of total size n on alphabet [1, {\sigma}] can be computed from the Burrows-Wheeler transformed collection in O(n log {\sigma}) time using o(n log {\sigma}) bits of working space on top of the input and output. Our result improves (on small alphabets) and generalizes (to string collections) the previous solution from Beller et al., which required O(n) bits of extra working space. We also show how to merge the BWTs of two collections of total size n within the same time and space bounds. The procedure at the core of our algorithms can be used to enumerate suffix tree intervals in succinct space from the BWT, which is of independent interest. An engineered implementation of our first algorithm on DNA alphabet induces the LCP of a large (16 GiB) collection of short (100 bases) reads at a rate of 2.92 megabases per second using in total 1.5 Bytes per base in RAM. Our second algorithm merges the BWTs of two short-reads collections of 8 GiB each at a rate of 1.7 megabases per second and uses 0.625 Bytes per base in RAM. An extension of this algorithm that computes also the LCP array of the merged collection processes the data at a rate of 1.48 megabases per second and uses 1.625 Bytes per base in RAM.
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