Evidence map›Paper›PMID 30815668›Full record

ReviewBriefings in bioinformatics2020

New approaches for metagenome assembly with short reads.

Martin Ayling, Matthew D Clark, Richard M Leggett

Abstract readReview
In one paragraph

Review in Briefings in bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers.

0numbers the graph read from it
0cells of the map it votes in
106citing 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

106 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Quantitative metagenomics using a portable protocol.Applied and environmental microbiology · 2026
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Metagenomic Assembly and Gene Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

46 more citing papers are in PubMed but not listed here.

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

3 authors.

Martin AylingEarlham Institute, Norwich Research Park, Norwich, UK.
Matthew D ClarkNatural History Museum, London, UK.
Richard M LeggettEarlham Institute, Norwich Research Park, Norwich, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/CSP17270/1Biotechnology and Biological Sciences Research Council BB/M004805/1Biotechnology and Biological Sciences Research Council BBS/E/T/000PR9817
6 · The paper itself

Abstract

In recent years, the use of longer range read data combined with advances in assembly algorithms has stimulated big improvements in the contiguity and quality of genome assemblies. However, these advances have not directly transferred to metagenomic data sets, as assumptions made by the single genome assembly algorithms do not apply when assembling multiple genomes at varying levels of abundance. The development of dedicated assemblers for metagenomic data was a relatively late innovation and for many years, researchers had to make do using tools designed for single genomes. This has changed in the last few years and we have seen the emergence of a new type of tool built using different principles. In this review, we describe the challenges inherent in metagenomic assemblies and compare the different approaches taken by these novel assembly tools.

Indexed as

MetagenomeAlgorithmsAnimalsHigh-Throughput Nucleotide SequencingHumansMicrobiotaPlantsSequence Analysis, DNAalgorithmsassemblyMetagenomicssequencing

Identifiers

PMID30815668
PMCPMC7299287

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.