Literature DB >> 33346148

VarBen: Generating in Silico Reference Data Sets for Clinical Next-Generation Sequencing Bioinformatics Pipeline Evaluation.

Ziyang Li1, Shuangsang Fang2, Rui Zhang3, Lijia Yu3, Jiawei Zhang1, Dechao Bu2, Liang Sun2, Yi Zhao4, Jinming Li5.   

Abstract

Next-generation sequencing is increasingly being adopted as a valuable method for the detection of somatic variants in clinical oncology. However, it is still challenging to reach a satisfactory level of robustness and standardization in clinical practice when using the currently available bioinformatics pipelines to detect variants from raw sequencing data. Moreover, appropriate reference data sets are lacking for clinical bioinformatics pipeline development, validation, and proficiency testing. Herein, we developed the Variant Benchmark tool (VarBen), an open-source software for variant simulation to generate customized reference data sets by directly editing the original sequencing reads. VarBen can introduce a variety of variants, including single-nucleotide variants, small insertions and deletions, and large structural variants, into targeted, exome, or whole-genome sequencing data, and can handle sequencing data from both the Illumina and Ion Torrent sequencing platforms. To demonstrate the feasibility and robustness of VarBen, we performed variant simulation on different sequencing data sets and compared the simulated variants with real-world data. The validation study showed that the simulated data are highly comparable to real-world data and that VarBen is a reliable tool for variant simulation. In addition, our collaborative study of somatic variant calling in 20 laboratories emphasizes the need for laboratories to evaluate their bioinformatics pipelines with customized reference data sets. VarBen may help users develop and validate their bioinformatics pipelines using locally generated sequencing data.
Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2020        PMID: 33346148     DOI: 10.1016/j.jmoldx.2020.11.010

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  2 in total

1.  Creation of an Expert Curated Variant List for Clinical Genomic Test Development and Validation: A ClinGen and GeT-RM Collaborative Project.

Authors:  Emma Wilcox; Steven M Harrison; Edward Lockhart; Karl Voelkerding; Ira M Lubin; Heidi L Rehm; Lisa V Kalman; Birgit Funke
Journal:  J Mol Diagn       Date:  2021-08-09       Impact factor: 5.568

2.  Deciphering complex genome rearrangements in C. elegans using short-read whole genome sequencing.

Authors:  Tatiana Maroilley; Xiao Li; Matthew Oldach; Francesca Jean; Susan J Stasiuk; Maja Tarailo-Graovac
Journal:  Sci Rep       Date:  2021-09-14       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.