ArticleFrontiers in cell and developmental biology2021
Fast and Accurate Classification of Meta-Genomics Long Reads With deSAMBA.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A review of computational approaches for metagenomics by long-read sequencing.Science China. Life sciences · 2026Review
- Computational Tools and Resources for Long-read Metagenomic Sequencing Using Nanopore and PacBio.Genomics, proteomics & bioinformatics · 2025Review
- Advancing metagenomic classification with NABAS+: a novel alignment-based approach.NAR genomics and bioinformatics · 2025Article
- Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities.Scientific data · 2024Article
- Comparative analysis of metagenomic classifiers for long-read sequencing datasets.BMC bioinformatics · 2024Article
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7 authors.
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Abstract
There is still a lack of fast and accurate classification tools to identify the taxonomies of noisy long reads, which is a bottleneck to the use of the promising long-read metagenomic sequencing technologies. Herein, we propose de Bruijn graph-based Sparse Approximate Match Block Analyzer (deSAMBA), a tailored long-read classification approach that uses a novel pseudo alignment algorithm based on sparse approximate match block (SAMB). Benchmarks on real sequencing datasets demonstrate that deSAMBA enables to achieve high yields and fast speed simultaneously, which outperforms state-of-the-art tools and has many potentials to cutting-edge metagenomics studies.
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