Academic Journal
Interpreting Microbial Species–Area Relationships: Effects of Sequence Data Processing Algorithms and Fitting Models.
| Title: | Interpreting Microbial Species–Area Relationships: Effects of Sequence Data Processing Algorithms and Fitting Models. |
|---|---|
| Authors: | Qi, Fu-Liang, Deng, Wei, Cheng, Yi-Ting, Yang, Xiao-Yan, Li, Na, Xiao, Wen |
| Source: | Microorganisms; Mar2025, Vol. 13 Issue 3, p635, 12p |
| Subject Terms: | Nucleotide sequencing, Data structures, Microbial diversity, Electronic data processing, Algorithms |
| Abstract: | In the study of Species–Area Relationships (SARs) in microorganisms, outcome discrepancies primarily stem from divergent high-throughput sequencing data processing algorithms and their combinations with different fitting models. This paper investigates the impacts and underlying causes of using diverse sequence data processing algorithms in microbial SAR studies, as well as compatibility issues that arise between different algorithms and fitting models. The findings indicate that the balancing strategies employed by different algorithms can result in variations in the calculations of alpha and beta diversity, thereby influencing the SARs of microorganisms. Crucially, incompatibilities exist between algorithms and models, with no consistently optimal combination identified. Based on these insights, we recommend prioritizing the use of the DADA2 algorithm in conjunction with a power model, which demonstrates greater compatibility. This study serves as a comprehensive comparison and reference for fundamental methods in microbial SAR research. Future microbial SAR studies should carefully select the most appropriate algorithms and models based on specific research objectives and data structures. [ABSTRACT FROM AUTHOR] |
| Copyright of Microorganisms is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://resolver.ebsco.com/c/fiv2js/result?sid=EBSCO:edb&genre=article&issn=20762607&ISBN=&volume=13&issue=3&date=20250301&spage=635&pages=635-646&title=Microorganisms&atitle=Interpreting%20Microbial%20Species%E2%80%93Area%20Relationships%3A%20Effects%20of%20Sequence%20Data%20Processing%20Algorithms%20and%20Fitting%20Models.&aulast=Qi%2C%20Fu-Liang&id=DOI:10.3390/microorganisms13030635 Name: Full Text Finder (for New FTF UI) (ns324271) Category: fullText Text: Full Text Finder MouseOverText: Full Text Finder |
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| Items | – Name: Title Label: Title Group: Ti Data: Interpreting Microbial Species–Area Relationships: Effects of Sequence Data Processing Algorithms and Fitting Models. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Qi%2C+Fu-Liang%22">Qi, Fu-Liang</searchLink><br /><searchLink fieldCode="AR" term="%22Deng%2C+Wei%22">Deng, Wei</searchLink><br /><searchLink fieldCode="AR" term="%22Cheng%2C+Yi-Ting%22">Cheng, Yi-Ting</searchLink><br /><searchLink fieldCode="AR" term="%22Yang%2C+Xiao-Yan%22">Yang, Xiao-Yan</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Na%22">Li, Na</searchLink><br /><searchLink fieldCode="AR" term="%22Xiao%2C+Wen%22">Xiao, Wen</searchLink> – Name: TitleSource Label: Source Group: Src Data: Microorganisms; Mar2025, Vol. 13 Issue 3, p635, 12p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Nucleotide+sequencing%22">Nucleotide sequencing</searchLink><br /><searchLink fieldCode="DE" term="%22Data+structures%22">Data structures</searchLink><br /><searchLink fieldCode="DE" term="%22Microbial+diversity%22">Microbial diversity</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In the study of Species–Area Relationships (SARs) in microorganisms, outcome discrepancies primarily stem from divergent high-throughput sequencing data processing algorithms and their combinations with different fitting models. This paper investigates the impacts and underlying causes of using diverse sequence data processing algorithms in microbial SAR studies, as well as compatibility issues that arise between different algorithms and fitting models. The findings indicate that the balancing strategies employed by different algorithms can result in variations in the calculations of alpha and beta diversity, thereby influencing the SARs of microorganisms. Crucially, incompatibilities exist between algorithms and models, with no consistently optimal combination identified. Based on these insights, we recommend prioritizing the use of the DADA2 algorithm in conjunction with a power model, which demonstrates greater compatibility. This study serves as a comprehensive comparison and reference for fundamental methods in microbial SAR research. Future microbial SAR studies should carefully select the most appropriate algorithms and models based on specific research objectives and data structures. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Microorganisms is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/microorganisms13030635 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 635 Subjects: – SubjectFull: Nucleotide sequencing Type: general – SubjectFull: Data structures Type: general – SubjectFull: Microbial diversity Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Algorithms Type: general Titles: – TitleFull: Interpreting Microbial Species–Area Relationships: Effects of Sequence Data Processing Algorithms and Fitting Models. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Qi, Fu-Liang – PersonEntity: Name: NameFull: Deng, Wei – PersonEntity: Name: NameFull: Cheng, Yi-Ting – PersonEntity: Name: NameFull: Yang, Xiao-Yan – PersonEntity: Name: NameFull: Li, Na – PersonEntity: Name: NameFull: Xiao, Wen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20762607 Numbering: – Type: volume Value: 13 – Type: issue Value: 3 Titles: – TitleFull: Microorganisms Type: main |
| ResultId | 1 |