» Articles » PMID: 31324872

Comprehensive Evaluation and Characterisation of Short Read General-purpose Structural Variant Calling Software

Overview
Journal Nat Commun
Specialty Biology
Date 2019 Jul 21
PMID 31324872
Citations 129
Authors
Affiliations
Soon will be listed here.
Abstract

In recent years, many software packages for identifying structural variants (SVs) using whole-genome sequencing data have been released. When published, a new method is commonly compared with those already available, but this tends to be selective and incomplete. The lack of comprehensive benchmarking of methods presents challenges for users in selecting methods and for developers in understanding algorithm behaviours and limitations. Here we report the comprehensive evaluation of 10 SV callers, selected following a rigorous process and spanning the breadth of detection approaches, using high-quality reference cell lines, as well as simulations. Due to the nature of available truth sets, our focus is on general-purpose rather than somatic callers. We characterise the impact on performance of event size and type, sequencing characteristics, and genomic context, and analyse the efficacy of ensemble calling and calibration of variant quality scores. Finally, we provide recommendations for both users and methods developers.

Citing Articles

Unraveling MECP2 structural variants in previously elusive Rett syndrome cases through IGV interpretation.

Poleg T, Hadar N, Heimer G, Dolgin V, Aminov I, Safran A NPJ Genom Med. 2025; 10(1):23.

PMID: 40082422 PMC: 11906642. DOI: 10.1038/s41525-025-00481-9.


Systematic benchmarking of tools for structural variation detection using short- and long-read sequencing data in pigs.

He S, Song B, Tang Y, Qu X, Li X, Yang X iScience. 2025; 28(3):111983.

PMID: 40060913 PMC: 11889634. DOI: 10.1016/j.isci.2025.111983.


Investigation of a pathogenic inversion in UNC13D and comprehensive analysis of chromosomal inversions across diverse datasets.

Bozkurt-Yozgatli T, Lun M, Bengtsson J, Sezerman U, Chinn I, Coban-Akdemir Z Eur J Hum Genet. 2025; .

PMID: 40021841 DOI: 10.1038/s41431-025-01817-w.


Benchmarking, detection, and genotyping of structural variants in a population of whole-genome assemblies using the SVGAP pipeline.

Hu M, Wan P, Chen C, Tang S, Chen J, Wang L bioRxiv. 2025; .

PMID: 39975360 PMC: 11839052. DOI: 10.1101/2025.02.07.637096.


Comparisons of performances of structural variants detection algorithms in solitary or combination strategy.

Duan D, Cheng C, Huang Y, Chung A, Chen P, Chen Y PLoS One. 2025; 20(2):e0314982.

PMID: 39913463 PMC: 11801633. DOI: 10.1371/journal.pone.0314982.


References
1.
Chen K, Wallis J, McLellan M, Larson D, Kalicki J, Pohl C . BreakDancer: an algorithm for high-resolution mapping of genomic structural variation. Nat Methods. 2009; 6(9):677-81. PMC: 3661775. DOI: 10.1038/nmeth.1363. View

2.
Schroder J, Wirawan A, Schmidt B, Papenfuss A . CLOVE: classification of genomic fusions into structural variation events. BMC Bioinformatics. 2017; 18(1):346. PMC: 5520322. DOI: 10.1186/s12859-017-1760-3. View

3.
Parikh H, Mohiyuddin M, Lam H, Iyer H, Chen D, Pratt M . svclassify: a method to establish benchmark structural variant calls. BMC Genomics. 2016; 17:64. PMC: 4715349. DOI: 10.1186/s12864-016-2366-2. View

4.
Hormozdiari F, Hajirasouliha I, McPherson A, Eichler E, Sahinalp S . Simultaneous structural variation discovery among multiple paired-end sequenced genomes. Genome Res. 2011; 21(12):2203-12. PMC: 3227108. DOI: 10.1101/gr.120501.111. View

5.
Rausch T, Zichner T, Schlattl A, Stutz A, Benes V, Korbel J . DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics. 2012; 28(18):i333-i339. PMC: 3436805. DOI: 10.1093/bioinformatics/bts378. View