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September 18, 2025Genome biologyOpen Access

A comprehensive benchmarking of adaptive sampling tools for nanopore sequencing

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Authors

LYLang YangYLYanfeng LinPLPeihan Li

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Overview

Evaluation of six adaptive sampling tools shows diverse performance in enriching and depleting target reads.

Key Points

  • The study revealed coverage depths of targets increased from 1.50- to 4.86-fold across tools tested.
  • The optimal strategy combined Guppy for base calling and minimap2 for read alignment, yielding high accuracy.
  • In using a nucleotide-alignment-based approach, tools such as MinKNOW excelled in adaptive sampling scenarios.
  • Deep learning methods demonstrated superior accuracy and speed in read ejection compared to traditional approaches.

Cite This Study

Yang et al. (2025) studied this question.

synapsesocial.com/papers/68d46ccf31b076d99fa6925bhttps://doi.org/10.1186/s13059-025-03729-w
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Expectations and Realities of Adaptive Sampling in Nanopore Sequencing2026
  2. 2Flexible and rapid validation of structural variation using adaptive sampling2025
  3. 3A systematic benchmark of bioinformatics methods for single-cell and spatial RNA-seq Nanopore long-read data2025 · 2 citations
  4. 4Flexible and rapid validation of structural variation using adaptive sampling2026
  5. 5A mapping-free NLP-based technique for sequence search in Nanopore long-reads2024