Improved Approximation Ratios for the Shortest Common Superstring Problem with Reverse Complements
Ryosuke Yamano, Tetsuo Shibuya

TL;DR
This paper improves approximation ratios for the Shortest Common Superstring problem with Reverse Complements (SCS-RC), a bioinformatics problem, by extending existing algorithms and providing the first formal bounds for this variant.
Contribution
It extends MGREEDY and TGREEDY algorithms to SCS-RC, achieving better approximation ratios of 3.75 and 2.875, respectively, and provides the first formal guarantees for SCS-RC.
Findings
MGREEDY extension achieves 3.75-approximation
TGREEDY extension achieves 2.875-approximation
First formal approximation bounds for SCS-RC
Abstract
The Shortest Common Superstring (SCS) problem asks for the shortest string that contains each of a given set of strings as a substring. Its reverse-complement variant, the Shortest Common Superstring problem with Reverse Complements (SCS-RC), naturally arises in bioinformatics applications, where for each input string, either the string itself or its reverse complement must appear as a substring of the superstring. The well-known MGREEDY algorithm for the standard SCS constructs a superstring by first computing an optimal cycle cover on the overlap graph and then concatenating the strings corresponding to the cycles, while its refined variant, TGREEDY, further improves the approximation ratio. Although the original 4- and 3-approximation bounds of these algorithms have been successively improved for the standard SCS, no such progress has been made for the reverse-complement setting. A…
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Taxonomy
TopicsGenome Rearrangement Algorithms · Algorithms and Data Compression · DNA and Biological Computing
