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Due to the increased availability of large datasets of biological sequences,the tools for sequence comparison are now relying on efficient alignment-freeapproaches to a greater extent. Most of the alignment-free approaches requirethe computation of statistics of the sequences in the dataset. Suchcomputations become impractical in internal memory when very large collectionsof long sequences are considered. In this paper, we present a new conceptualdata structure, the colored longest common prefix array (cLCP), that allows toefficiently tackle several problems with an alignment-free approach. In fact,we show that such a data structure can be computed via sequential scans insemi-external memory. By using cLCP, we propose an efficient lightweightstrategy to solve the multi-string Average Common Substring (ACS) problem, thatconsists in the pairwise comparison of a single string against a collection of$m$ strings simultaneously, in order to obtain $m$ ACS induced distances.Experimental results confirm the effectiveness of our approach.

The colored longest common prefix array computed via sequential scans