Evidence map›Paper›PMID 25983555›Full record

ReviewBioinformatics and biology insights2015

Metagenomics: tools and insights for analyzing next-generation sequencing data derived from biodiversity studies.

Anastasis Oulas, Christina Pavloudi, Paraskevi Polymenakou, Georgios A Pavlopoulos, Nikolas Papanikolaou, Georgios Kotoulas, Christos Arvanitidis, Ioannis Iliopoulos

Abstract readReview
In one paragraph

Review in Bioinformatics and biology insights, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed, 1 pooled it
–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

120 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. AMB Express · 2026
    Article
  5. International journal of microbiology · 2026
    Review
  6. Article
  7. Article
  8. Visualizing metagenomic and metatranscriptomic data: A comprehensive review.Computational and structural biotechnology journal · 2024
    Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

60 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

8 authors.

Anastasis OulasInstitute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece.
Christina PavloudiInstitute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece. ; Department of Biology, University of Ghent, Ghent, Belgium. ; Department of Microbial Ecophysiology, University of Bremen, Bremen, Germany.
Paraskevi PolymenakouInstitute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece.
Georgios A PavlopoulosDivision of Basic Sciences, University of Crete, Medical School, Heraklion, Crete, Greece.
Nikolas PapanikolaouDivision of Basic Sciences, University of Crete, Medical School, Heraklion, Crete, Greece.
Georgios KotoulasInstitute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece.
Christos ArvanitidisInstitute of Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece.
Ioannis IliopoulosDivision of Basic Sciences, University of Crete, Medical School, Heraklion, Crete, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in next-generation sequencing (NGS) have allowed significant breakthroughs in microbial ecology studies. This has led to the rapid expansion of research in the field and the establishment of "metagenomics", often defined as the analysis of DNA from microbial communities in environmental samples without prior need for culturing. Many metagenomics statistical/computational tools and databases have been developed in order to allow the exploitation of the huge influx of data. In this review article, we provide an overview of the sequencing technologies and how they are uniquely suited to various types of metagenomic studies. We focus on the currently available bioinformatics techniques, tools, and methodologies for performing each individual step of a typical metagenomic dataset analysis. We also provide future trends in the field with respect to tools and technologies currently under development. Moreover, we discuss data management, distribution, and integration tools that are capable of performing comparative metagenomic analyses of multiple datasets using well-established databases, as well as commonly used annotation standards.

Indexed as

computational toolsdata analysismetagenomicsnext-generation sequencing

Identifiers

PMID25983555
PMCPMC4426941

What OpenQuestion holds

Textmetadata
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.