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Fast and robust metagenomic sequence comparison through sparse chaining with skani
Nature Methods ( IF 36.1 ) Pub Date : 2023-09-21 , DOI: 10.1038/s41592-023-02018-3
Jim Shaw 1 , Yun William Yu 1, 2, 3
Affiliation  

Sequence comparison tools for metagenome-assembled genomes (MAGs) struggle with high-volume or low-quality data. We present skani (https://github.com/bluenote-1577/skani), a method for determining average nucleotide identity (ANI) via sparse approximate alignments. skani outperforms FastANI in accuracy and speed (>20× faster) for fragmented, incomplete MAGs. skani can query genomes against >65,000 prokaryotic genomes in seconds and 6 GB memory. skani unlocks higher-resolution insights for extensive, noisy metagenomic datasets.



中文翻译:


通过 skani 的稀疏链接进行快速、稳健的宏基因组序列比较



用于宏基因组组装基因组 (MAG) 的序列比较工具难以处理大量或低质量的数据。我们提出了 skani (https://github.com/bluenote-1577/skani),一种通过稀疏近似比对确定平均核苷酸同一性 (ANI) 的方法。对于碎片化、不完整的 MAG,skani 在准确性和速度方面优于 FastANI(快 3E20 倍)。 skani 可以在几秒钟内查询 >65,000 个原核基因组的基因组,并使用 6 GB 内存。 skani 为广泛、嘈杂的宏基因组数据集提供了更高分辨率的见解。

更新日期:2023-09-21
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