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OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement

Overview of attention for article published in BMC Bioinformatics, June 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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13 X users

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39 Mendeley
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Title
OrthoReD: a rapid and accurate orthology prediction tool with low computational requirement
Published in
BMC Bioinformatics, June 2017
DOI 10.1186/s12859-017-1726-5
Pubmed ID
Authors

Kai Battenberg, Ernest K. Lee, Joanna C. Chiu, Alison M. Berry, Daniel Potter

Abstract

Identifying orthologous genes is an initial step required for phylogenetics, and it is also a common strategy employed in functional genetics to find candidates for functionally equivalent genes across multiple species. At the same time, in silico orthology prediction tools often require large computational resources only available on computing clusters. Here we present OrthoReD, an open-source orthology prediction tool with accuracy comparable to published tools that requires only a desktop computer. The low computational resource requirement of OrthoReD is achieved by repeating orthology searches on one gene of interest at a time, thereby generating a reduced dataset to limit the scope of orthology search for each gene of interest. The output of OrthoReD was highly similar to the outputs of two other published orthology prediction tools, OrthologID and/or OrthoDB, for the three dataset tested, which represented three phyla with different ranges of species diversity and different number of genomes included. Median CPU time for ortholog prediction per gene by OrthoReD executed on a desktop computer was <15 min even for the largest dataset tested, which included all coding sequences of 100 bacterial species. With high-throughput sequencing, unprecedented numbers of genes from non-model organisms are available with increasing need for clear information about their orthologies and/or functional equivalents in model organisms. OrthoReD is not only fast and accurate as an orthology prediction tool, but also gives researchers flexibility in the number of genes analyzed at a time, without requiring a high-performance computing cluster.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 28%
Researcher 9 23%
Student > Bachelor 4 10%
Student > Master 3 8%
Other 2 5%
Other 5 13%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 46%
Biochemistry, Genetics and Molecular Biology 10 26%
Computer Science 2 5%
Environmental Science 1 3%
Immunology and Microbiology 1 3%
Other 1 3%
Unknown 6 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 15 September 2020.
All research outputs
#4,385,376
of 23,801,098 outputs
Outputs from BMC Bioinformatics
#1,646
of 7,445 outputs
Outputs of similar age
#75,396
of 318,163 outputs
Outputs of similar age from BMC Bioinformatics
#21
of 115 outputs
Altmetric has tracked 23,801,098 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,445 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 77% 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 318,163 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 76% of its contemporaries.
We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.