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A pile of pipelines: An overview of the bioinformatics software for metabarcoding data analyses

Overview of attention for article published in Molecular Ecology Resources, August 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#25 of 1,975)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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138 X users

Citations

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9 Dimensions

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106 Mendeley
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Title
A pile of pipelines: An overview of the bioinformatics software for metabarcoding data analyses
Published in
Molecular Ecology Resources, August 2023
DOI 10.1111/1755-0998.13847
Pubmed ID
Authors

Ali Hakimzadeh, Alejandro Abdala Asbun, Davide Albanese, Maria Bernard, Dominik Buchner, Benjamin Callahan, J. Gregory Caporaso, Emily Curd, Christophe Djemiel, Mikael Brandström Durling, Vasco Elbrecht, Zachary Gold, Hyun S. Gweon, Mehrdad Hajibabaei, Falk Hildebrand, Vladimir Mikryukov, Eric Normandeau, Ezgi Özkurt, Jonathan M. Palmer, Géraldine Pascal, Teresita M. Porter, Daniel Straub, Martti Vasar, Tomáš Větrovský, Haris Zafeiropoulos, Sten Anslan

Abstract

Environmental DNA (eDNA) metabarcoding has gained growing attention as a strategy for monitoring biodiversity in ecology. However, taxa identifications produced through metabarcoding require sophisticated processing of high-throughput sequencing data from taxonomically informative DNA barcodes. Various sets of universal and taxon-specific primers have been developed, extending the usability of metabarcoding across archaea, bacteria and eukaryotes. Accordingly, a multitude of metabarcoding data analysis tools and pipelines have also been developed. Often, several developed workflows are designed to process the same amplicon sequencing data, making it somewhat puzzling to choose one among the plethora of existing pipelines. However, each pipeline has its own specific philosophy, strengths and limitations, which should be considered depending on the aims of any specific study, as well as the bioinformatics expertise of the user. In this review, we outline the input data requirements, supported operating systems and particular attributes of thirty-two amplicon processing pipelines with the goal of helping users to select a pipeline for their metabarcoding projects.

X Demographics

X Demographics

The data shown below were collected from the profiles of 138 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 106 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 106 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 16%
Researcher 15 14%
Student > Master 11 10%
Student > Bachelor 8 8%
Student > Postgraduate 6 6%
Other 17 16%
Unknown 32 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 25%
Environmental Science 16 15%
Biochemistry, Genetics and Molecular Biology 14 13%
Veterinary Science and Veterinary Medicine 4 4%
Unspecified 2 2%
Other 6 6%
Unknown 37 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 82. 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 08 November 2023.
All research outputs
#534,412
of 25,905,864 outputs
Outputs from Molecular Ecology Resources
#25
of 1,975 outputs
Outputs of similar age
#10,088
of 362,695 outputs
Outputs of similar age from Molecular Ecology Resources
#2
of 43 outputs
Altmetric has tracked 25,905,864 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,975 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.8. This one has done particularly well, scoring higher than 98% 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 362,695 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 97% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.