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Article: Challenges in benchmarking metagenomic profilers

TitleChallenges in benchmarking metagenomic profilers
Authors
Issue Date2021
Citation
Nature Methods, 2021, v. 18, n. 6, p. 618-626 How to Cite?
AbstractAccurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling.
Persistent Identifierhttp://hdl.handle.net/10722/311512
ISSN
2021 Impact Factor: 47.990
2020 SCImago Journal Rankings: 19.469
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorSun, Zheng-
dc.contributor.authorHuang, Shi-
dc.contributor.authorZhang, Meng-
dc.contributor.authorZhu, Qiyun-
dc.contributor.authorHaiminen, Niina-
dc.contributor.authorCarrieri, Anna Paola-
dc.contributor.authorVázquez-Baeza, Yoshiki-
dc.contributor.authorParida, Laxmi-
dc.contributor.authorKim, Ho Cheol-
dc.contributor.authorKnight, Rob-
dc.contributor.authorLiu, Yang Yu-
dc.date.accessioned2022-03-22T11:54:07Z-
dc.date.available2022-03-22T11:54:07Z-
dc.date.issued2021-
dc.identifier.citationNature Methods, 2021, v. 18, n. 6, p. 618-626-
dc.identifier.issn1548-7091-
dc.identifier.urihttp://hdl.handle.net/10722/311512-
dc.description.abstractAccurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling.-
dc.languageeng-
dc.relation.ispartofNature Methods-
dc.titleChallenges in benchmarking metagenomic profilers-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1038/s41592-021-01141-3-
dc.identifier.pmid33986544-
dc.identifier.pmcidPMC8184642-
dc.identifier.scopuseid_2-s2.0-85105779673-
dc.identifier.volume18-
dc.identifier.issue6-
dc.identifier.spage618-
dc.identifier.epage626-
dc.identifier.eissn1548-7105-
dc.identifier.isiWOS:000650075300002-

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