In Silico Proficiency Testing for Clinical Next-Generation Sequencing

被引:24
|
作者
Duncavage, Eric J. [1 ]
Abel, Haley J. [2 ]
Pfeifer, John D. [1 ]
机构
[1] Washington Univ, Sch Med, Dept Pathol, Campus Box 8118,660 S Euclid Ave, St Louis, MO 63110 USA
[2] Washington Univ, Sch Med, Dept Genet, St Louis, MO 63110 USA
来源
JOURNAL OF MOLECULAR DIAGNOSTICS | 2017年 / 19卷 / 01期
关键词
LIBRARY PREPARATION; READ SIMULATOR; QUALITY; GENOME; VALIDATION; MODEL;
D O I
10.1016/j.jmoldx.2016.09.005
中图分类号
R36 [病理学];
学科分类号
100104 ;
摘要
Quality assurance for clinical next-generation sequencing (NGS) based assays is difficult given the complex methods and the range of sequence variants such assays can detect. As the number and range of mutations detected by clinical NGS assays has increased, it is difficult to apply standard analytespecific proficiency testing (PT). Most current proficiency testing challenges for NGS are methods-based PT surveys that use DNA from reference samples engineered to harbor specific mutations that test both sequence generation and bioinformatics analysis. These methods-based PTs are Limited by the number and types of mutations that can be physically introduced into a single DNA sample. In silico proficiency testing, which evaluates only the bioinformatics component of NGS assays, is a recently introduced PT method that allows for evaluation of numerous mutations spanning a range of variant classes. In silico PT data sets can be generated from simulated or actual sequencing data and are used to test alignment through variant detection and annotation steps. In silico PT has several advantages over the use of physical samples, including greater flexibility in tested variants, the ability to design laboratory-specific challenges, and Lower costs. Herein, we review the use of in silico PT as an alternative to traditional methods-based PT as it is evolving in oncology applications and discuss how the approach is applicable more broadly.
引用
收藏
页码:35 / 42
页数:8
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