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In this paper we propose a flexible and lightweight technique for mergingcompressed indices based on variants of Burrows-Wheeler transform (BWT), thusaddressing the need for algorithms that compute compressed indices over largecollections using a limited amount of working memory. Merge procedures make itpossible to use an incremental strategy for building large indices based onmerging indices for progressively larger subcollections.  Starting with a known lightweight algorithm for merging BWTs [Holt andMcMillan, Bionformatics 2014], we show how to modify it in order to merge, orcompute from scratch, also the Longest Common Prefix (LCP) array. We thenexpand our technique for merging compressed tries and circular/permutermcompressed indices, two compressed data structures for which there werehitherto no known merging algorithms.

Lightweight merging of compressed indices based on BWT variants