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Related Experiment Video

Updated: Mar 28, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Control for stochastic sampling variation and qualitative sequencing error in next generation sequencing.

Thomas Blomquist¹, Erin L Crawford², Jiyoun Yeo²

¹Department of Pathology, University of Toledo Health Sciences Campus, Toledo, OH 43614.

Biomolecular Detection and Quantification

|December 23, 2015

Summary

This summary is machine-generated.

Synthetic internal standards (IS) improve Next-Generation Sequencing (NGS) accuracy by controlling for sampling errors and sequencing errors. This enables reliable clinical diagnostics for copy number and actionable mutations.

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Clinical Next-Generation Sequencing (NGS) faces challenges with stochastic sampling, library preparation biases, and sequencing errors.
Accurate quantification and error control are crucial for reliable clinical diagnostics.

Purpose of the Study:

To develop and test hypotheses addressing analytical variation in NGS.
To evaluate the role of synthetic internal standards (IS) in controlling for sampling and sequencing errors.

Main Methods:

Utilized Monte Carlo simulations to model assay coefficient of variation (CV) based on sampling events.
Tested models against NGS data from specimens with known molecule inputs and sequence counts.
Assessed concordance of technical sequencing error frequencies between target native templates (NT) and competitive synthetic IS.

Main Results:

A Monte Carlo model incorporating both sampling events best predicted CV, explaining 74% of assay variance.
Observed error frequencies and types in IS were highly concordant with those in NTs (R² = 0.93).

Conclusions:

Synthetic competitive IS effectively control for stochastic sampling during library preparation and sequencing.
IS also control for qualitative errors introduced during library preparation and sequencing.
These controls facilitate accurate clinical diagnostic reporting, including confidence limits, limit of detection, and actionable mutation frequencies.