Evidence map›Paper›PMID 38603597›Full record

ArticleBioinformatics (Oxford, England)2024

SimReadUntil for benchmarking selective sequencing algorithms on ONT devices.

Maximilian Mordig, Gunnar Rätsch, André Kahles

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Enrichment techniques for clinical metagenomics.Frontiers in cellular and infection microbiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Maximilian MordigBiomedical Informatics Group, Department of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.ORCID 0000-0002-5731-484X
Gunnar RätschBiomedical Informatics Group, Department of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.ORCID 0000-0001-5486-8532
André KahlesBiomedical Informatics Group, Department of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.ORCID 0000-0002-3411-0692

Funding

Max Planck ETH Center for Learning SystemsSNF #200550
6 · The paper itself

Abstract

motivationThe Oxford Nanopore Technologies (ONT) ReadUntil API enables selective sequencing, which aims to selectively favor interesting over uninteresting reads, e.g. to deplete or enrich certain genomic regions. The performance gain depends on the selective sequencing decision-making algorithm (SSDA) which decides whether to reject a read, stop receiving a read, or wait for more data. Since real runs are time-consuming and costly, simulating the ONT sequencer with support for the ReadUntil API is highly beneficial for comparing and optimizing new SSDAs. Existing software like MinKNOW and UNCALLED only return raw signal data, are memory-intensive, require huge and often unavailable multi-fast5 files (≥100GB) and are not clearly documented.

resultsWe present the ONT device simulator SimReadUntil that takes a set of full reads as input, distributes them to channels and plays them back in real time including mux scans, channel gaps and blockages, and allows to reject reads as well as stop receiving data from them. Our modified ReadUntil API provides the basecalled reads rather than the raw signal, reducing computational load and focusing on the SSDA rather than on basecalling. Tuning the parameters of tools like ReadFish and ReadBouncer becomes easier because a GPU for basecalling is no longer required. We offer various methods to extract simulation parameters from a sequencing summary file and adapt ReadFish to replicate one of their enrichment experiments. SimReadUntil's gRPC interface allows standardized interaction with a wide range of programming languages. AVAILABILITY AND IMPLEMENTATION: Code and fully worked examples are available on GitHub (https://github.com/ratschlab/sim_read_until).

Indexed as

AlgorithmsSoftwareHigh-Throughput Nucleotide SequencingNanopore SequencingSequence Analysis, DNA

Identifiers

PMID38603597
PMCPMC11065473

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.