| Autor: |
Xiongbin Kang, Jialu Xu, Xiao Luo, Alexander Schönhuth |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Genome Biology, Vol 24, Iss 1, Pp 1-39 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1474-760X |
| DOI: |
10.1186/s13059-023-03112-7 |
| Popis: |
Abstract Although generally superior, hybrid approaches for correcting errors in third-generation sequencing (TGS) reads, using next-generation sequencing (NGS) reads, mistake haplotype-specific variants for errors in polyploid and mixed samples. We suggest HERO, as the first “hybrid-hybrid” approach, to make use of both de Bruijn graphs and overlap graphs for optimal catering to the particular strengths of NGS and TGS reads. Extensive benchmarking experiments demonstrate that HERO improves indel and mismatch error rates by on average 65% (27 $$\sim$$ ∼ 95%) and 20% (4 $$\sim$$ ∼ 61%). Using HERO prior to genome assembly significantly improves the assemblies in the majority of the relevant categories. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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