Evidence map›Paper›PMID 37975872›Full record

ArticleBioinformatics (Oxford, England)2023

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

Nikolai Romashchenko, Benjamin Linard, Fabio Pardi, Eric Rivals

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Nikolai RomashchenkoLIRMM, University of Montpellier, CNRS, Montpellier, France.ORCID 0000-0002-2264-5219
Benjamin LinardLIRMM, University of Montpellier, CNRS, Montpellier, France.ORCID 0000-0002-5555-898X
Fabio PardiLIRMM, University of Montpellier, CNRS, Montpellier, France.ORCID 0000-0001-8084-1464
Eric RivalsLIRMM, University of Montpellier, CNRS, Montpellier, France.ORCID 0000-0003-3791-3973
Centre National de la Recherche Scientifique · FR

Funding

European Union's Horizon 2020French Ministry of ResearchFrench National Agency for Research
6 · The paper itself

Abstract

motivationPhylogenetic 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.

resultsWe 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. AVAILABILITY AND IMPLEMENTATION: 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.

Indexed as

AlgorithmsSoftwareBase SequencePhylogenySequence Analysis, DNA

Identifiers

PMID37975872
PMCPMC10701097
OpenAlexW4388760829

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.