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Related Experiment Video

Updated: Apr 11, 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

Denoising DNA deep sequencing data-high-throughput sequencing errors and their correction.

David Laehnemann, Arndt Borkhardt, Alice Carolyn McHardy

Briefings in Bioinformatics

|May 31, 2015

Summary

Understanding sequencing errors is crucial for accurate genetic analysis. This study surveys error profiles across six major platforms, aiding in distinguishing true variations from technical artifacts.

Keywords:

bias error correction error model error profile high-throughput sequencing next-generation sequencing

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Last Updated: Apr 11, 2026

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Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

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Published on: September 13, 2018

Area of Science:

Genomics
Bioinformatics

Background:

High-throughput sequencing platforms generate errors that can be mistaken for true genetic variation.
Accurate identification of genetic variations is vital for numerous downstream analyses.

Purpose of the Study:

To characterize error profiles of six prominent high-throughput sequencing platforms.
To provide guidance on selecting appropriate error correction tools based on data properties.

Main Methods:

Surveyed error profiles of 454 pyrosequencing, Complete Genomics, Illumina, Ion Torrent, Pacific Biosciences, and Oxford Nanopore sequencing.
Reviewed various error removal programs, their models, and statistical techniques.

Main Results:

Identified distinct random and systematic error profiles for each surveyed sequencing platform.
Highlighted the assumptions and data types relevant to different error correction tools.

Conclusions:

Knowledge of platform-specific error profiles is essential for distinguishing true genetic variation from technical artifacts.
Future development of error correction and variant calling tools can benefit from integrating existing knowledge and approaches.