NanoPrePro: a fully equipped, fast, and memory-efficient preprocessor for nanopore transcriptomic sequencing

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Authors: Chia-Chen Chu, Jhong-He Yu, Shang‐Che Kuo, Fan‐Wei Yang, Chia-Chang Lin, Chang-Hung Chen, Yichen Wu, Cing Shih, Ying‐Hsuan Sun, Te‐Lun Mai, Ying‐Lan Chen, Hsin-Hung Lin
+2 more Jung-Chen Su, Ying‐Chung Jimmy Lin
Cited by: 0
References: 58

Abstract

NanoPrePro is a streamlined read preprocessor specifically designed for high precision in identifying full-length reads from Oxford Nanopore Technology (ONT) transcriptomic sequencing results, achieved through the precise identification of adapters/primers. However, the preprocessing of ONT reads has been a long-term neglected and ambiguous area without thorough and systematic investigation. Here, we developed NanoPrePro that outperformed the current best preprocessor, Pychopper, using simulated and real datasets. Through sequence similarity, adapter/primer location, and adapter/primer length, NanoPrePro exerted a self-optimizing function to extract the best parameters in each sequencing file for users to customize their analyses. Furthermore, NanoPrePro shows a 38-times faster speed with less memory cost. NanoPrePro can be regarded as the state-of-the-art preprocessor with forward adaptability of ONT sequencing.

Fields of Study & Subjects

Genomics and Phylogenetic Studies Single-cell and spatial transcriptomics Algorithms and Data Compression

Publication details

Journal / source
Briefings in Bioinformatics
Volume
27
Issue
1
Publication date
1 January 2026
Language
EN