A 1.5-Approximation Algorithm for Two-Sided Scaffold Filling

The scaffold filling problem aims to set up the whole genomes by filling those missing genes into the scaffolds to optimize a similarity measure of genomes. A typical and frequently used measure for the similarity of two genomes is the number of common adjacencies. One-sided scaffold filling is given by a scaffold and a whole genome, and asks to fill the missing genes into that scaffold to result in such a genome that the number of common adjacencies between it and the given genome is maximized. Two-sided scaffold filling is given by two scaffolds, and asks to fill the missing genes into those two scaffolds respectively to result in such two genomes that the number of common adjacencies between them is maximized. One-sided scaffold filling can be approximated to 5/4 by now. However, the algorithmic progress for two-sided scaffold filling seems rare. What we know for two-sided scaffold filling is a 2-approximation algorithm by now. In this paper, we propose a new algorithm for two-sided scaffold filling which can achieve a performance ratio of 3/2 in O(N^3) time, where N is the number of genes in an output genome. An example can be given to show that the performance ratio 3/2 for this algorithm is actually tight.