A Hybrid Approach to Optimize the Number of Recombinations in Ancestral Recombination Graphs

Building ancestral recombination graphs (ARG) with minimum number of recombination events for large datasets is a challenging problem. We have proposed ARG4WG and REARG heuristic algorithm for constructing ARGs with thousands of whole genome sequences. However, these algorithms do not result in ARGs with minimal number of recombination events. In this work, we propose GAMARG algorithm, an improvement of ARG4WG, to optimize the number of recombination events in ARG building process. Experiment with different datasets showed that GAMARG algorithm outperforms other heuristic algorithms in building ARGs for large datasets. It also is much better than other heuristic algorithms and comparable to exhaustive search methods for small datasets.