DEMINERS enables clinical metagenomics and comparative transcriptomic analysis by increasing throughput and accuracy of nanopore direct RNA sequencing

Nanopore direct RNA sequencing (DRS) is a powerful tool for RNA biology but suffers from low basecalling accuracy, low throughput, and high input requirements. We present DEMINERS, a novel DRS toolkit combining an RNA multiplexing workflow, a Random Forest-based barcode classifier, and an optimized convolutional neural network basecaller with species-specific training. DEMINERS enables accurate demultiplexing of up to 24 samples, reducing RNA input and runtime. Applications include clinical metagenomics, cancer transcriptomics, and parallel transcriptomic comparisons, uncovering microbial diversity in COVID-19 and m<sup>6</sup>A's role in malaria and glioma. DEMINERS offers a robust, high-throughput solution for precise transcript and RNA modification analysis.

Authors

Institutions

Publication Details

Journal
Genome biology
Published
2025-03-28
DOI
https://doi.org/10.1186/s13059-025-03536-3
Citations
9
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
7.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DEMINERS enables clinical metagenomics and comparative transcriptomic analysis by increasing throughput and accuracy of nanopore direct RNA sequencing

Juan Jiang, Junwei Song, Tingfeng Chen, Defu Liu et al.
9 citations
Genome biology
RNA modifications and cancer
7.25
article

DEMINERS enables clinical metagenomics and comparative transcriptomic analysis by increasing throughput and accuracy of nanopore direct RNA sequencing

Juan Jiang, Junwei Song, Tingfeng Chen, Defu Liu, Jia Geng, Weizhen Zhu, Jingwen Lin, Zijie Xu, Mutian Chen, Bojiang Chen, Yu Zhong, Guiqin Song, Qingxin Yang, Yuan Wang, Jing Wang, Li Chen, Lu Chen, Juan Zhou, Zhifeng He, Yuancun Zhao, Wanqin Zeng, Binwu Ying, Han-cheng Wei, Chao Tang, L. Lin, Kepan Linghu, Chuan Chen, Dan Zhang
article en
9 citations

Abstract

Nanopore direct RNA sequencing (DRS) is a powerful tool for RNA biology but suffers from low basecalling accuracy, low throughput, and high input requirements. We present DEMINERS, a novel DRS toolkit combining an RNA multiplexing workflow, a Random Forest-based barcode classifier, and an optimized convolutional neural network basecaller with species-specific training. DEMINERS enables accurate demultiplexing of up to 24 samples, reducing RNA input and runtime. Applications include clinical metagenomics, cancer transcriptomics, and parallel transcriptomic comparisons, uncovering microbial diversity in COVID-19 and m<sup>6</sup>A's role in malaria and glioma. DEMINERS offers a robust, high-throughput solution for precise transcript and RNA modification analysis.

Genome biologyVol. 26(1)
North Sichuan Medical University (CN), Sichuan University (CN), West China Hospital of Sichuan University (CN), State Key Laboratory of Biotherapy
Openalex Percentile: Top 3%
RNA modifications and cancer
7.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.