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Related Experiment Video

Updated: Jan 21, 2026

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Published on: March 11, 2020

Genomic language model mitigates chimera artifacts in nanopore direct RNA sequencing.

Yangyang Li¹, Ting-You Wang¹, Qingxiang Guo¹

¹Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Nature Communications

|January 19, 2026

Summary

DeepChopper accurately removes adapter sequences from nanopore direct RNA sequencing reads. This improves transcript annotation and gene fusion detection, making nanopore sequencing more reliable for transcriptomics.

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Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Sequencing of mRNA from Whole Blood using Nanopore Sequencing

Published on: June 3, 2019

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Chimera artifacts in nanopore direct RNA sequencing (dRNA-seq) reduce accuracy in transcript annotation and gene fusion detection.
Existing basecalling models cannot identify or fix these artifacts, limiting dRNA-seq utility.

Purpose of the Study:

To develop a method for identifying and removing adapter sequences from dRNA-seq long reads.
To enhance the reliability and accuracy of nanopore dRNA-seq for transcriptomics.

Main Methods:

Developed DeepChopper, a genomic language model for adapter sequence identification and removal.
DeepChopper operates on base-called dRNA-seq reads, independent of raw signal or alignment data.
The model precisely removes adapter-bridged artifacts with single-base resolution.

Main Results:

DeepChopper effectively identifies and removes adapter sequences from dRNA-seq long reads.
The method eliminates adapter-bridged artifacts without requiring raw signal or alignment information.
Demonstrated enhancement in the accuracy of downstream transcriptomics analyses.

Conclusions:

DeepChopper significantly improves the accuracy of nanopore dRNA-seq data.
The tool enhances transcript annotation and gene fusion detection capabilities.
DeepChopper establishes nanopore dRNA-seq as a more robust tool for transcriptomics research.