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Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....

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Related Experiment Video

Updated: Mar 11, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

In Silico Proficiency Testing for Clinical Next-Generation Sequencing.

Eric J Duncavage¹, Haley J Abel², John D Pfeifer¹

¹Department of Pathology, Washington University School of Medicine, St. Louis, Missouri.

The Journal of Molecular Diagnostics : JMD

|November 19, 2016

Summary

This summary is machine-generated.

Quality assurance for clinical next-generation sequencing (NGS) is challenging. In silico proficiency testing (PT) offers a flexible, cost-effective alternative to traditional methods-based PT for evaluating bioinformatics in NGS assays.

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Area of Science:

Genomics
Bioinformatics
Clinical Diagnostics

Background:

Clinical next-generation sequencing (NGS) assays require robust quality assurance.
Increasing complexity and variant detection range of NGS assays challenge traditional proficiency testing (PT).
Current methods-based PTs, using engineered DNA, are limited by the number and types of mutations that can be physically introduced.

Purpose of the Study:

To review the evolving use of in silico proficiency testing (PT) as an alternative to traditional methods-based PT for clinical NGS assays.
To highlight the advantages of in silico PT in oncology and its broader applicability.

Main Methods:

In silico PT evaluates the bioinformatics component of NGS assays using simulated or actual sequencing data.
Data sets are used to test alignment, variant detection, and annotation steps.
This approach contrasts with methods-based PTs that rely on physical samples with engineered mutations.

Main Results:

In silico PT allows for the evaluation of numerous mutations across various variant classes.
Advantages include greater flexibility in tested variants and the ability to design laboratory-specific challenges.
In silico PT offers a more cost-effective solution compared to traditional methods-based PT.

Conclusions:

In silico PT is a viable and advantageous alternative to traditional methods-based PT for NGS quality assurance.
The approach is particularly relevant in oncology applications and has broader potential.
In silico PT enhances the evaluation of the bioinformatics pipeline in clinical sequencing assays.