ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information

BMC Bioinformatics

Proceedings

Satoru Miyano¹  Tomohiro Yasuda¹  Masao Nagasaki¹  Shin Suzuki¹  Yuichi Shiraishi¹ 

[1] Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, 108-8639, Minatoku, Tokyo, Japan;

关键词: Reference Genome;    Read Length;    Tandem Duplication;    Coverage Approach;    True Call;   

DOI  :  10.1186/1471-2105-12-S14-S7

来源: Springer

【 摘 要 】

BackgroundStructural variations (SVs) change the structure of the genome and are therefore the causes of various diseases. Next-generation sequencing allows us to obtain a multitude of sequence data, some of which can be used to infer the position of SVs.MethodsWe developed a new method and implementation named ClipCrop for detecting SVs with single-base resolution using soft-clipping information. A soft-clipped sequence is an unmatched fragment in a partially mapped read. To assess the performance of ClipCrop with other SV-detecting tools, we generated various patterns of simulation data – SV lengths, read lengths, and the depth of coverage of short reads – with insertions, deletions, tandem duplications, inversions and single nucleotide alterations in a human chromosome. For comparison, we selected BreakDancer, CNVnator and Pindel, each of which adopts a different approach to detect SVs, e.g. discordant pair approach, depth of coverage approach and split read approach, respectively.ResultsOur method outperformed BreakDancer and CNVnator in both discovering rate and call accuracy in any type of SV. Pindel offered a similar performance as our method, but our method crucially outperformed for detecting small duplications. From our experiments, ClipCrop infer reliable SVs for the data set with more than 50 bases read lengths and 20x depth of coverage, both of which are reasonable values in current NGS data set.ConclusionsClipCrop can detect SVs with higher discovering rate and call accuracy than any other tool in our simulation data set.

【 授权许可】

Unknown   
© Suzuki et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.