ArticleComputational and structural biotechnology journal2025
LongReadSum: A fast and flexible quality control and signal summarization tool for long-read sequencing data.
Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Review
- Long-Read Transcriptome Sequencing and Functional Validation Reveals Novel and Oncogenic Gene Fusions in Fusion Panel-Negative Gliomas.bioRxiv : the preprint server for biology · 2026Article
- Emergence of OXA-48-like Carbapenemase-ProducingAntibiotics (Basel, Switzerland) · 2026Article
- The Role of Nucleotide Sequencing in Natural Product Drug Discovery.Journal of natural products · 2025Review
- Combining panel-based and whole-transcriptome-based gene fusion detection by long-read sequencing.Cell reports methods · 2025Article
- A comparative evaluation of computational models for RNA modification detection using nanopore sequencing with RNA004 chemistry.Briefings in bioinformatics · 2025Article
- A Comparative Evaluation of Computational Models for RNA modification detection using Nanopore sequencing with RNA004 Chemistry.bioRxiv : the preprint server for biology · 2025Article
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Abstract
While several well-established quality control (QC) tools exist for short-read sequencing data, there is a general paucity of computational tools that efficiently deliver comprehensive metrics across a wide range of long-read sequencing data formats, such as Oxford Nanopore (ONT) POD5, ONT FAST5, ONT basecall summary, Pacific Biosciences (PacBio) unaligned BAM, and Illumina Complete Long Read (ICLR) FASTQ file formats. In addition to nucleotide sequence information, some file formats such as POD5 contain raw signal information used for base calling, while other file formats such as aligned BAM contain alignments to a linear reference genome or transcriptome and may also contain base modification information. There is currently no single available QC tool capable of summarizing each of these features. Furthermore, high-performance tools are required to efficiently process the growing data volumes from long-read sequencing platforms. To address these challenges, here we present LongReadSum, a high-performance tool for generating a summary QC report for major types of long-read sequencing data. We also demonstrate a few examples using LongReadSum to analyze cDNA sequencing, direct RNA sequencing, ONT reduced representation methylation sequencing (RRMS), and whole genome sequencing (WGS) data.
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