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- Publisher Website: 10.1038/s41592-021-01141-3
- Scopus: eid_2-s2.0-85105779673
- PMID: 33986544
- WOS: WOS:000650075300002
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Article: Challenges in benchmarking metagenomic profilers
Title | Challenges in benchmarking metagenomic profilers |
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Authors | |
Issue Date | 2021 |
Citation | Nature Methods, 2021, v. 18, n. 6, p. 618-626 How to Cite? |
Abstract | Accurate 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 Identifier | http://hdl.handle.net/10722/311512 |
ISSN | 2023 Impact Factor: 36.1 2023 SCImago Journal Rankings: 14.796 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Sun, Zheng | - |
dc.contributor.author | Huang, Shi | - |
dc.contributor.author | Zhang, Meng | - |
dc.contributor.author | Zhu, Qiyun | - |
dc.contributor.author | Haiminen, Niina | - |
dc.contributor.author | Carrieri, Anna Paola | - |
dc.contributor.author | Vázquez-Baeza, Yoshiki | - |
dc.contributor.author | Parida, Laxmi | - |
dc.contributor.author | Kim, Ho Cheol | - |
dc.contributor.author | Knight, Rob | - |
dc.contributor.author | Liu, Yang Yu | - |
dc.date.accessioned | 2022-03-22T11:54:07Z | - |
dc.date.available | 2022-03-22T11:54:07Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Nature Methods, 2021, v. 18, n. 6, p. 618-626 | - |
dc.identifier.issn | 1548-7091 | - |
dc.identifier.uri | http://hdl.handle.net/10722/311512 | - |
dc.description.abstract | Accurate 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.language | eng | - |
dc.relation.ispartof | Nature Methods | - |
dc.title | Challenges in benchmarking metagenomic profilers | - |
dc.type | Article | - |
dc.description.nature | link_to_OA_fulltext | - |
dc.identifier.doi | 10.1038/s41592-021-01141-3 | - |
dc.identifier.pmid | 33986544 | - |
dc.identifier.pmcid | PMC8184642 | - |
dc.identifier.scopus | eid_2-s2.0-85105779673 | - |
dc.identifier.volume | 18 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 618 | - |
dc.identifier.epage | 626 | - |
dc.identifier.eissn | 1548-7105 | - |
dc.identifier.isi | WOS:000650075300002 | - |