Evidence map›Paper›PMID 29696589›Full record

ReviewProtein & cell2018

Single-cell metagenomics: challenges and applications.

Yuan Xu, Fangqing Zhao

Open access · diamondAbstract readReview
In one paragraph

Review in Protein & cell, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
4.1field-weighted citation impact, top 5% 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.

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

48 citing papers in PubMed, 116 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. How genomics can help unravel the evolution of endophytic fungi.World journal of microbiology & biotechnology · 2025
    Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. Facial disbiosis and UV filters.Archives of dermatological research · 2024
    Article
  18. Targeted whole-genome recovery of single viral species in a complex environmental sample.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  19. Article
  20. Review
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

2 authors at 1 institution in 1 country.

Yuan XuComputational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China.
Fangqing ZhaoComputational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing, 100101, China. zhfq@biols.ac.cn.
Beijing Institute of Genomics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the development of high throughput sequencing and single-cell genomics technologies, many uncultured bacterial communities have been dissected by combining these two techniques. Especially, by simultaneously leveraging of single-cell genomics and metagenomics, researchers can greatly improve the efficiency and accuracy of obtaining whole genome information from complex microbial communities, which not only allow us to identify microbes but also link function to species, identify subspecies variations, study host-virus interactions and etc. Here, we review recent developments and the challenges need to be addressed in single-cell metagenomics, including potential contamination, uneven sequence coverage, sequence chimera, genome assembly and annotation. With the development of sequencing and computational methods, single-cell metagenomics will undoubtedly broaden its application in various microbiome studies.

Indexed as

MetagenomicsAnimalsBacteriaComputational BiologyHigh-Throughput Nucleotide SequencingHumansSingle-Cell Analysisbioinformaticsmetagenomicssingle-cell genomics

Identifiers

PMID29696589
PMCPMC5960468
OpenAlexW2799490241

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.