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rMFilter:通过嵌合读段过滤加速基于长读段的结构变异检测

rMFilter: acceleration of long read-based structure variation calling by chimeric read filtering.

作者信息

Liu Bo, Jiang Tao, Yiu S M, Li Junyi, Wang Yadong

机构信息

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

Department of Computer Science, The University of Hong Kong, Hong Kong, China.

出版信息

Bioinformatics. 2017 Sep 1;33(17):2750-2752. doi: 10.1093/bioinformatics/btx279.

Abstract

MOTIVATION

Long read sequencing technologies provide new opportunities to investigate genome structural variations (SVs) more accurately. However, the state-of-the-art SV calling pipelines are computational intensive and the applications of long reads are restricted.

RESULTS

We propose a local region match-based filter (rMFilter) to efficiently nail down chimeric noisy long reads based on short token matches within local genomic regions. rMFilter is able to substantially accelerate long read-based SV calling pipelines without loss of effectiveness. It can be easily integrated into current long read-based pipelines to facilitate SV studies.

AVAILABILITY AND IMPLEMENTATION

The C ++ source code of rMFilter is available at https://github.com/hitbc/rMFilter .

CONTACT

ydwang@hit.edu.cn.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

长读长测序技术为更准确地研究基因组结构变异(SVs)提供了新机会。然而,当前最先进的SV检测流程计算量很大,长读长的应用受到限制。

结果

我们提出了一种基于局部区域匹配的过滤器(rMFilter),以基于局部基因组区域内的短令牌匹配有效地确定嵌合噪声长读长。rMFilter能够在不损失有效性的情况下大幅加速基于长读长的SV检测流程。它可以轻松集成到当前基于长读长的流程中,以促进SV研究。

可用性和实现

rMFilter的C++ 源代码可在https://github.com/hitbc/rMFilter获得。

联系方式

ydwang@hit.edu.cn

补充信息

补充数据可在《生物信息学》在线获取。

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