Evidence map›Paper›PMID 28673025›Full record

ReviewBriefings in bioinformatics2019

Alignment-free inference of hierarchical and reticulate phylogenomic relationships.

Guillaume Bernard, Cheong Xin Chan, Yao-Ban Chan, Xin-Yi Chua, Yingnan Cong, James M Hogan, Stefan R Maetschke, Mark A Ragan

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed.

  1. Review
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  10. How to optimally sample a sequence for rapid analysis.Bioinformatics (Oxford, England) · 2023
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  11. Review
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  19. Alignment-free sequence comparison for virus genomes based on location correlation coefficient.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2021
    Article
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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

8 authors.

Guillaume BernardInstitute for Molecular Bioscience.
Cheong Xin ChanUniversity of Queensland.
Yao-Ban ChanUniversity of Melbourne.
Xin-Yi ChuaQFAB Bioinformatics.
Yingnan CongUniversity of Queensland.
James M HoganQueensland University of Technology.
Stefan R MaetschkeIBM Research Australia.
Mark A RaganInstitute for Molecular Bioscience.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We are amidst an ongoing flood of sequence data arising from the application of high-throughput technologies, and a concomitant fundamental revision in our understanding of how genomes evolve individually and within the biosphere. Workflows for phylogenomic inference must accommodate data that are not only much larger than before, but often more error prone and perhaps misassembled, or not assembled in the first place. Moreover, genomes of microbes, viruses and plasmids evolve not only by tree-like descent with modification but also by incorporating stretches of exogenous DNA. Thus, next-generation phylogenomics must address computational scalability while rethinking the nature of orthogroups, the alignment of multiple sequences and the inference and comparison of trees. New phylogenomic workflows have begun to take shape based on so-called alignment-free (AF) approaches. Here, we review the conceptual foundations of AF phylogenetics for the hierarchical (vertical) and reticulate (lateral) components of genome evolution, focusing on methods based on k-mers. We reflect on what seems to be successful, and on where further development is needed.

Indexed as

Evolution, MolecularGenomePhylogenyAlgorithmsAnimalsHumansMicrobiotaModels, GeneticSequence AlignmentSequence Analysis, DNAVirusesalignment-freeD2 statisticsk-merlateral genetic transferphylogenomicsTF–IDF

Identifiers

PMID28673025
PMCPMC6433738

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LicenceCC BY
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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.