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Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity

Overview of attention for article published in Microbiome, May 2015
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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61 X users
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Title
Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity
Published in
Microbiome, May 2015
DOI 10.1186/s40168-015-0081-x
Pubmed ID
Authors

Yan He, J Gregory Caporaso, Xiao-Tao Jiang, Hua-Fang Sheng, Susan M Huse, Jai Ram Rideout, Robert C Edgar, Evguenia Kopylova, William A Walters, Rob Knight, Hong-Wei Zhou

Abstract

The operational taxonomic unit (OTU) is widely used in microbial ecology. Reproducibility in microbial ecology research depends on the reliability of OTU-based 16S ribosomal subunit RNA (rRNA) analyses. Here, we report that many hierarchical and greedy clustering methods produce unstable OTUs, with membership that depends on the number of sequences clustered. If OTUs are regenerated with additional sequences or samples, sequences originally assigned to a given OTU can be split into different OTUs. Alternatively, sequences assigned to different OTUs can be merged into a single OTU. This OTU instability affects alpha-diversity analyses such as rarefaction curves, beta-diversity analyses such as distance-based ordination (for example, Principal Coordinate Analysis (PCoA)), and the identification of differentially represented OTUs. Our results show that the proportion of unstable OTUs varies for different clustering methods. We found that the closed-reference method is the only one that produces completely stable OTUs, with the caveat that sequences that do not match a pre-existing reference sequence collection are discarded. As a compromise to the factors listed above, we propose using an open-reference method to enhance OTU stability. This type of method clusters sequences against a database and includes unmatched sequences by clustering them via a relatively stable de novo clustering method. OTU stability is an important consideration when analyzing microbial diversity and is a feature that should be taken into account during the development of novel OTU clustering methods.

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X Demographics

The data shown below were collected from the profiles of 61 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 227 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 3%
Australia 2 <1%
France 2 <1%
Indonesia 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Sweden 1 <1%
Thailand 1 <1%
Belgium 1 <1%
Other 0 0%
Unknown 210 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 21%
Researcher 42 19%
Student > Master 29 13%
Student > Bachelor 25 11%
Student > Doctoral Student 18 8%
Other 25 11%
Unknown 40 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 93 41%
Biochemistry, Genetics and Molecular Biology 34 15%
Environmental Science 12 5%
Medicine and Dentistry 9 4%
Computer Science 7 3%
Other 22 10%
Unknown 50 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 36. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 August 2022.
All research outputs
#1,108,567
of 25,390,970 outputs
Outputs from Microbiome
#332
of 1,751 outputs
Outputs of similar age
#13,470
of 280,377 outputs
Outputs of similar age from Microbiome
#5
of 16 outputs
Altmetric has tracked 25,390,970 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,751 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 38.3. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,377 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.