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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

SKSV: ultrafast structural variation detection from circular consensus sequencing reads

Yadong Liu¹, Tao Jiang¹, Junhao Su^1,2

¹Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China.

Bioinformatics (Oxford, England)

|May 8, 2021

Abstract

Summary:

Circular consensus sequencing 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 And Implementation:

SKSV is available from https://github.com/ydLiu-HIT/SKSV.

Supplementary Information:

Supplementary data are available at Bioinformatics online.

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