A Genomic Language Model for Chimera Artifact Detection in Nanopore Direct RNA Sequencing

Yangyang Li*, Tingyou Wang*, Qingxiang Guo, Yanan Ren, Xiaotong Lu, Qi Cao, Rendong Yang
Northwestern University
*Indicates Equal Contribution
Paper Code bioRxiv

Overview of the architecture of the DeepChopper model.

Abstract

Chimera artifacts in nanopore direct RNA sequencing (dRNA-seq) can significantly distort transcriptome analyses, yet their detection and removal remain challenging due to limitations in existing basecalling models. We present DeepChopper, a genomic language model that precisely identifies and removes adapter sequences from base-called dRNA-seq long reads at single-base resolution, operating independently of raw signal or alignment information to effectively eliminate chimeric read artifacts. By removing these artifacts, DeepChopper substantially improves the accuracy of critical downstream analyses, such as transcript annotation and gene fusion detection, thereby enhancing the reliability and utility of nanopore dRNA-seq for transcriptomics research.

BibTeX

@article {Li2024.10.23.619929,
        author = {Li, Yangyang and Wang, Ting-You and Guo, Qingxiang and Ren, Yanan and Lu, Xiaotong and Cao, Qi and Yang, Rendong},
        title = {A Genomic Language Model for Chimera Artifact Detection in Nanopore Direct RNA Sequencing},
        elocation-id = {2024.10.23.619929},
        year = {2024},
        doi = {10.1101/2024.10.23.619929},
        publisher = {Cold Spring Harbor Laboratory},
        abstract = {Chimera artifacts in nanopore direct RNA sequencing (dRNA-seq) data can confound transcriptome analyses, yet no existing tools are capable of detecting and removing them due to limitations in basecalling models. We present DeepChopper, a genomic language model that accurately identifies and eliminates adapter sequences within base-called dRNA-seq reads, effectively removing chimeric read artifacts. DeepChopper significantly improves critical downstream analyses, including transcript annotation and gene fusion detection, enhancing the reliability and utility of nanopore dRNA-seq for transcriptomics research.Competing Interest StatementThe authors have declared no competing interest.},
        URL = {https://www.biorxiv.org/content/early/2024/10/25/2024.10.23.619929},
        eprint = {https://www.biorxiv.org/content/early/2024/10/25/2024.10.23.619929.full.pdf},
        journal = {bioRxiv}
}