Nguyen Thi Phuong Thao
ABSTRACT
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.
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Index Terms
- A Hybrid Approach to Optimize the Number of Recombinations in Ancestral Recombination Graphs
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Building Ancestral Recombination Graphs for Whole Genomes
We propose a heuristic algorithm, called ARG4WG, to build plausible ancestral recombination graphs ARGs from thousands of whole genome samples. By using the longest shared end for recombination inference, ARG4WG constructs ARGs with small numbers of ...
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