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Updated: Jun 4, 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

Technology-specific error signatures in the 1000 Genomes Project data.

Michael Nothnagel¹, Alexander Herrmann, Andreas Wolf

¹Institute of Medical Informatics and Statistics, Christian-Albrechts University, Brunswiker Str. 10, 24105 Kiel, Germany, nothnagel@medinfo.uni-kiel.de

|February 24, 2011

Summary

Next-generation sequencing (NGS) platforms have different error profiles. Using multiple platforms for variant calling significantly reduces false positives, improving data validity and potentially lowering costs.

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

Genomics
Bioinformatics
Human Genetics

Background:

Next-generation sequencing (NGS) is crucial for understanding human genetic variability.
Accurate identification of single-nucleotide variants (SNVs) is essential for reliable genetic studies.

Purpose of the Study:

To develop a statistical framework for assessing the fidelity of common NGS platforms.
To compare the error profiles and accuracy of different NGS technologies.

Main Methods:

Utilized aligned DNA sequence data from HapMap samples within the 1000 Genomes Project.
Developed a statistical framework to evaluate the accuracy of three common NGS platforms.
Compared NGS-inferred SNVs against confirmed HapMap variants.

Main Results:

Observed distinct error profiles across the three evaluated NGS platforms.
Identified a significant proportion of false positives (3-17%) in SNVs called by single platforms.
Demonstrated that consensus calling across multiple platforms reduced error rates to 1-4%.

Conclusions:

Multiple NGS platforms offer improved accuracy and cost-efficiency compared to single-platform approaches.
The choice of NGS platform should align with specific application requirements and desired error rates.
Stringent data quality control is imperative for validating results from NGS-based studies.