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EPIK: precise and scalable evolutionary placement with informative k-mers

Overview of attention for article published in Bioinformatics, November 2023
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  • Above-average Attention Score compared to outputs of the same age (57th percentile)
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Article details
Title
EPIK: precise and scalable evolutionary placement with informative k-mers
Published in
Bioinformatics, November 2023
DOI 10.1093/bioinformatics/btad692
Pubmed ID
Authors
Abstract

Phylogenetic placement enables phylogenetic analysis of massive collections of newly sequenced DNA, when de novo tree inference is too unreliable or inefficient. Assuming that a high-quality reference tree is available, the idea is to seek the correct placement of the new sequences in that tree. Recently, alignment-free approaches to phylogenetic placement have emerged, both to circumvent the need to align the new sequences and to avoid the calculations that typically follow the alignment step. A promising approach is based on the inference of k-mers that can be potentially related to the reference sequences, also called phylo-k-mers. However, its usage is limited by the time and memory-consuming stage of reference data preprocessing and the large numbers of k-mers to consider. We suggest a filtering method for selecting informative phylo-k-mers based on mutual information, which can significantly improve the efficiency of placement, at the cost of a small loss in placement accuracy. This method is implemented in IPK, a new tool for computing phylo-k-mers that significantly outperforms the software previously available. We also present EPIK, a new software for phylogenetic placement, supporting filtered phylo-k-mer databases. Our experiments on real-world data show that EPIK is the fastest phylogenetic placement tool available, when placing hundreds of thousands and millions of queries while still providing accurate placements. IPK and EPIK are freely available at https://github.com/phylo42/IPK and https://github.com/phylo42/EPIK. Both are implemented in C ++ and Python and supported on Linux and MacOS. Supplementary data are available at Bioinformatics online.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 2 22%
Researcher 2 22%
Professor > Associate Professor 1 11%
Professor 1 11%
Unknown 3 33%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 3 33%
Biochemistry, Genetics and Molecular Biology 1 11%
Medicine and Dentistry 1 11%
Unknown 4 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 04 December 2023.
All research outputs
#16,678,610
of 27,791,073 outputs
Outputs from Bioinformatics
#7,704
of 11,251 outputs
Outputs of similar age
#175,280
of 420,278 outputs
Outputs of similar age from Bioinformatics
#77
of 143 outputs
Altmetric has tracked 27,791,073 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,251 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 420,278 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.
We're also able to compare this research output to 143 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.