Literature DB >> 33963826

SKSV: ultrafast structural variation detection from circular consensus sequencing reads.

Yadong Liu1, Tao Jiang1, Junhao Su1,2, Bo Liu1, Tianyi Zang1, Yadong Wang1.   

Abstract

SUMMARY: Circular consensus sequencing (CCS) reads are promising for the comprehensive detection of structural variants (SVs). However, alignment-based SV calling pipelines are computationally intensive due to the generation of complete read-alignments and its post-processing. Herein, we propose a SKeleton-based analysis toolkit for Structural Variation detection (SKSV). Benchmarks on real and simulated datasets demonstrate that SKSV has an order of magnitude of faster speed than state-of-the-art SV calling approaches, moreover, it achieves higher F1 scores for various types of SVs. AVAILABILITY: SKSV is available from https://github.com/ydLiu-HIT/SKSV. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2021). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2021        PMID: 33963826     DOI: 10.1093/bioinformatics/btab341

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  2 in total

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Authors:  Ze-Gang Wei; Xing-Guo Fan; Hao Zhang; Xiao-Dan Zhang; Fei Liu; Yu Qian; Shao-Wu Zhang
Journal:  Front Genet       Date:  2022-05-05       Impact factor: 4.772

2.  Comprehensive evaluation of structural variant genotyping methods based on long-read sequencing data.

Authors:  Xiaoke Duan; Mingpei Pan; Shaohua Fan
Journal:  BMC Genomics       Date:  2022-04-23       Impact factor: 4.547

  2 in total

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