Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4752627 | Computational Biology and Chemistry | 2017 | 14 Pages |
Abstract
In this paper, we propose a new method named “PECC” to identify and correct misassembly errors in contigs based on the paired-end read distribution. PECC extracts sequence regions with lower paired-end reads supports and verifies them based on the distribution of paired-end supports. To validate the effectiveness of PECC, we applied PECC to the contigs produced by five popular assemblers on four real datasets, and we also carried out experiments to analyze the influences of PECC on scaffolding. The results show that PECC can reduce misassembly errors and improve the performance of scaffolding results, which demonstrate the promising applications of PECC in de novo assembly.
Related Topics
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Authors
Min Li, Binbin Wu, Xiaodong Yan, Junwei Luo, Yi Pan, Fang-Xiang Wu, Jianxin Wang,