基于BWT变体的压缩索引的轻量合并
Lightweight merging of compressed indices based on BWT variants
摘要：
在本文中，我们提出了一个灵活的和轻量级的技术合并压缩索引的基础上的变体的Burrows-Wheeler变换（BWT），从而解决了需要的算法，计算压缩索引的大型集合使用有限的工作内存。合并过程可以使用增量策略来构建大型索引，该策略基于合并索引以逐步增大子集合。从一个已知的用于合并BWT的轻量级算法开始[Holt和McMillan，Bionformatics 2014]，我们展示了如何修改它以合并或从头开始计算最长公共前缀（LCP）数组。然后，我们扩大我们的技术合并压缩尝试和循环/permuterm压缩索引，两个压缩的数据结构，迄今没有已知的合并算法。
英文摘要：
In this paper we propose a flexible and lightweight technique for merging compressed indices based on variants of Burrows-Wheeler transform (BWT), thus addressing the need for algorithms that compute compressed indices over large collections using a limited amount of working memory. Merge procedures make it possible to use an incremental strategy for building large indices based on merging indices for progressively larger subcollections. Starting with a known lightweight algorithm for merging BWTs [Holt and McMillan, Bionformatics 2014], we show how to modify it in order to merge, or compute from scratch, also the Longest Common Prefix (LCP) array. We then expand our technique for merging compressed tries and circular/permuterm compressed indices, two compressed data structures for which there were hitherto no known merging algorithms.
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