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TREE2FASTA: a flexible Perl script for batch extraction of FASTA sequences from exploratory phylogenetic trees

Overview of attention for article published in BMC Research Notes, March 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
10 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
13 Mendeley
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Title
TREE2FASTA: a flexible Perl script for batch extraction of FASTA sequences from exploratory phylogenetic trees
Published in
BMC Research Notes, March 2018
DOI 10.1186/s13104-018-3268-y
Pubmed ID
Authors

Thomas Sauvage, Sophie Plouviez, William E. Schmidt, Suzanne Fredericq

Abstract

The body of DNA sequence data lacking taxonomically informative sequence headers is rapidly growing in user and public databases (e.g. sequences lacking identification and contaminants). In the context of systematics studies, sorting such sequence data for taxonomic curation and/or molecular diversity characterization (e.g. crypticism) often requires the building of exploratory phylogenetic trees with reference taxa. The subsequent step of segregating DNA sequences of interest based on observed topological relationships can represent a challenging task, especially for large datasets. We have written TREE2FASTA, a Perl script that enables and expedites the sorting of FASTA-formatted sequence data from exploratory phylogenetic trees. TREE2FASTA takes advantage of the interactive, rapid point-and-click color selection and/or annotations of tree leaves in the popular Java tree-viewer FigTree to segregate groups of FASTA sequences of interest to separate files. TREE2FASTA allows for both simple and nested segregation designs to facilitate the simultaneous preparation of multiple data sets that may overlap in sequence content.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 15%
Student > Bachelor 2 15%
Student > Ph. D. Student 2 15%
Student > Master 2 15%
Researcher 1 8%
Other 1 8%
Unknown 3 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 15%
Engineering 2 15%
Veterinary Science and Veterinary Medicine 1 8%
Computer Science 1 8%
Biochemistry, Genetics and Molecular Biology 1 8%
Other 2 15%
Unknown 4 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 20 May 2020.
All research outputs
#1,905,690
of 23,025,074 outputs
Outputs from BMC Research Notes
#235
of 4,283 outputs
Outputs of similar age
#44,053
of 332,016 outputs
Outputs of similar age from BMC Research Notes
#8
of 109 outputs
Altmetric has tracked 23,025,074 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,283 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done particularly well, scoring higher than 94% 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 332,016 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 109 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 92% of its contemporaries.