RepAHR: an improved approach for de novo repeat identification by assembly of the high-frequency reads.
Xingyu LiaoXin GaoXiankai ZhangFang-Xiang WuJianxin WangPublished in: BMC bioinformatics (2020)
We test RepAHR on five data sets, and the experimental results show that RepAHR outperforms RepARK and REPdenovo for detecting repeats in terms of N50, reference alignment ratio, coverage ratio of reference, mask ratio of Repbase and some other metrics.