Evidence map›Paper›PMID 40928958›Full record

ArticleMicrobial genomics2025

AmpliconTyper - a tool for analysing ONT multiplex PCR data from environmental and other complex samples.

Anton Spadar, Jaspreet Mahindroo, Catherine Troman, Michael Owusu, Yaw Adu-Sarkodie, Ellis Owusu-Dabo, Dilip Abraham, Blossom Benny, Karthikeyan Govindan, Venkata Raghava Mohan and 3 more

Abstract read
In one paragraph

Article in Microbial genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Anton SpadarDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Jaspreet MahindrooMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
Catherine TromanMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
Michael OwusuCollege of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Yaw Adu-SarkodieCollege of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Ellis Owusu-DaboCollege of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Dilip AbrahamThe Wellcome Trust Research Laboratory, Christian Medical College, Vellore, India.
Blossom BennyThe Wellcome Trust Research Laboratory, Christian Medical College, Vellore, India.
Karthikeyan GovindanThe Wellcome Trust Research Laboratory, Christian Medical College, Vellore, India.
Venkata Raghava MohanDepartment of Community Health And Development, Christian Medical College, Vellore, India.
Zoe A DysonDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.
Nicholas GrasslyMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
Kathryn E HoltDepartment of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amplicon sequencing is a popular method for understanding the diversity of bacterial communities in samples containing multiple organisms as exemplified by 16S rRNA sequencing. Another application of amplicon sequencing includes multiplexing both primer sets and samples, allowing sequencing of multiple targets in multiple samples in the same sequencing run. Multiple tools exist to process the amplicon sequencing data produced via the short-read Illumina platform, but there are fewer options for long-read Oxford Nanopore Technologies (ONT) sequencing, or for processing data from environmental surveillance or other sources with many different organisms. We have developed AmpliconTyper (v0.1.28, DOI: 10.5281/zenodo.15045111) for analysing multiplex amplicon sequencing data from environmental (e.g. wastewater) or similarly complex samples, generated using ONT devices. The tool uses machine learning to classify sequencing reads into target and non-target organisms with very high specificity and sensitivity. The user can train models using public and/or user-generated data, which can subsequently be applied to analyse new data. The tool can also generate amplicon consensus sequences, as well as identify SNPs and report their genotype implications, such as association with lineages or antimicrobial resistance (AMR). The tool is freely available via Bioconda and GitHub (https://github.com/AntonS-bio/AmpliconTyper). AmpliconTyper allows robust identification of target organism reads in ONT-sequenced environmental samples and can identify user-specified lineage or AMR markers.

Indexed as

BacteriaHigh-Throughput Nucleotide SequencingMultiplex Polymerase Chain ReactionSoftwareEnvironmental MicrobiologyMachine LearningRNA, Ribosomal, 16SSequence Analysis, DNAWastewaterRNA, Ribosomal, 16SWastewaterampliconsenvironmental surveillancemultiplex PCROxford Nanopore Technologies

Identifiers

PMID40928958
PMCPMC12452170

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.