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使用 cuteSV 进行基于长读长的人类基因组结构变异检测。

Long-read-based human genomic structural variation detection with cuteSV.

机构信息

Center for Bioinformatics, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, Heilongjiang, China.

Nebula Genomics, Harbin, 150030, Heilongjiang, China.

出版信息

Genome Biol. 2020 Aug 3;21(1):189. doi: 10.1186/s13059-020-02107-y.

Abstract

Long-read sequencing is promising for the comprehensive discovery of structural variations (SVs). However, it is still non-trivial to achieve high yields and performance simultaneously due to the complex SV signatures implied by noisy long reads. We propose cuteSV, a sensitive, fast, and scalable long-read-based SV detection approach. cuteSV uses tailored methods to collect the signatures of various types of SVs and employs a clustering-and-refinement method to implement sensitive SV detection. Benchmarks on simulated and real long-read sequencing datasets demonstrate that cuteSV has higher yields and scaling performance than state-of-the-art tools. cuteSV is available at https://github.com/tjiangHIT/cuteSV .

摘要

长读测序在全面发现结构变异(SVs)方面具有广阔的前景。然而,由于嘈杂的长读序列中隐含的复杂 SV 特征,要同时实现高产率和高性能仍然具有挑战性。我们提出了 cuteSV,这是一种基于长读序列的敏感、快速和可扩展的 SV 检测方法。cuteSV 使用定制的方法来收集各种类型 SV 的特征,并采用聚类和细化方法来实现敏感的 SV 检测。在模拟和真实的长读测序数据集上的基准测试表明,cuteSV 比最先进的工具具有更高的产量和扩展性能。cuteSV 可在 https://github.com/tjiangHIT/cuteSV 上获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c515/7478186/da5c2df4a602/13059_2020_2107_Fig1_HTML.jpg

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