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Article: Melon: metagenomic long-read-based taxonomic identification and quantification using marker genes

TitleMelon: metagenomic long-read-based taxonomic identification and quantification using marker genes
Authors
KeywordsLong-read sequencing
Metagenomics
Taxonomic profiling
Issue Date1-Dec-2024
PublisherBioMed Central
Citation
Genome Biology, 2024, v. 25, n. 1 How to Cite?
Abstract

Long-read sequencing holds great potential for characterizing complex microbial communities, yet taxonomic profiling tools designed specifically for long reads remain lacking. We introduce Melon, a novel marker-based taxonomic profiler that capitalizes on the unique attributes of long reads. Melon employs a two-stage classification scheme to reduce computational time and is equipped with an expectation-maximization-based post-correction module to handle ambiguous reads. Melon achieves superior performance compared to existing tools in both mock and simulated samples. Using wastewater metagenomic samples, we demonstrate the applicability of Melon by showing it provides reliable estimates of overall genome copies, and species-level taxonomic profiles.


Persistent Identifierhttp://hdl.handle.net/10722/362213
ISSN
2012 Impact Factor: 10.288
2023 SCImago Journal Rankings: 7.197

 

DC FieldValueLanguage
dc.contributor.authorChen, Xi-
dc.contributor.authorYin, Xiaole-
dc.contributor.authorShi, Xianghui-
dc.contributor.authorYan, Weifu-
dc.contributor.authorYang, Yu-
dc.contributor.authorLiu, Lei-
dc.contributor.authorZhang, Tong-
dc.date.accessioned2025-09-20T00:30:49Z-
dc.date.available2025-09-20T00:30:49Z-
dc.date.issued2024-12-01-
dc.identifier.citationGenome Biology, 2024, v. 25, n. 1-
dc.identifier.issn1474-7596-
dc.identifier.urihttp://hdl.handle.net/10722/362213-
dc.description.abstract<p>Long-read sequencing holds great potential for characterizing complex microbial communities, yet taxonomic profiling tools designed specifically for long reads remain lacking. We introduce Melon, a novel marker-based taxonomic profiler that capitalizes on the unique attributes of long reads. Melon employs a two-stage classification scheme to reduce computational time and is equipped with an expectation-maximization-based post-correction module to handle ambiguous reads. Melon achieves superior performance compared to existing tools in both mock and simulated samples. Using wastewater metagenomic samples, we demonstrate the applicability of Melon by showing it provides reliable estimates of overall genome copies, and species-level taxonomic profiles.</p>-
dc.languageeng-
dc.publisherBioMed Central-
dc.relation.ispartofGenome Biology-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectLong-read sequencing-
dc.subjectMetagenomics-
dc.subjectTaxonomic profiling-
dc.titleMelon: metagenomic long-read-based taxonomic identification and quantification using marker genes -
dc.typeArticle-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/s13059-024-03363-y-
dc.identifier.pmid39160564-
dc.identifier.scopuseid_2-s2.0-85201542350-
dc.identifier.volume25-
dc.identifier.issue1-
dc.identifier.eissn1474-760X-
dc.identifier.issnl1474-7596-

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