Evidence map›Paper›PMID 28968737›Full record

ArticleBriefings in bioinformatics2019

Metagenomic assembly through the lens of validation: recent advances in assessing and improving the quality of genomes assembled from metagenomes.

Nathan D Olson, Todd J Treangen, Christopher M Hill, Victoria Cepeda-Espinoza, Jay Ghurye, Sergey Koren, Mihai Pop

Abstract readValidation Study
In one paragraph

Article 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 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing 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

78 citing papers in PubMed.

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  11. Analysis of metagenomic data.Nature reviews. Methods primers · 2025
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  19. KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2024
    Article
  20. Article

18 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

7 authors.

Nathan D Olson
Todd J Treangen
Christopher M Hill
Victoria Cepeda-Espinoza
Jay Ghurye
Sergey Koren
Mihai Pop

Funding

Algorithms and Software for the Assembly of Metagenomic DataR01AI100947 · NIAID · UNIV OF MARYLAND, COLLEGE PARK · PI POP, MIHAI · 2013 to 2025
$7.4M
Assembly and analysis software for exploring the human microbiomeR01HG004885 · NHGRI · UNIV OF MARYLAND, COLLEGE PARK · PI POP, MIHAI · 2008 to 2010
$888k
NHGRI NIH HHS R01 HG004885NIAID NIH HHS R01 AI100947
6 · The paper itself

Abstract

Metagenomic samples are snapshots of complex ecosystems at work. They comprise hundreds of known and unknown species, contain multiple strain variants and vary greatly within and across environments. Many microbes found in microbial communities are not easily grown in culture making their DNA sequence our only clue into their evolutionary history and biological function. Metagenomic assembly is a computational process aimed at reconstructing genes and genomes from metagenomic mixtures. Current methods have made significant strides in reconstructing DNA segments comprising operons, tandem gene arrays and syntenic blocks. Shorter, higher-throughput sequencing technologies have become the de facto standard in the field. Sequencers are now able to generate billions of short reads in only a few days. Multiple metagenomic assembly strategies, pipelines and assemblers have appeared in recent years. Owing to the inherent complexity of metagenome assembly, regardless of the assembly algorithm and sequencing method, metagenome assemblies contain errors. Recent developments in assembly validation tools have played a pivotal role in improving metagenomics assemblers. Here, we survey recent progress in the field of metagenomic assembly, provide an overview of key approaches for genomic and metagenomic assembly validation and demonstrate the insights that can be derived from assemblies through the use of assembly validation strategies. We also discuss the potential for impact of long-read technologies in metagenomics. We conclude with a discussion of future challenges and opportunities in the field of metagenomic assembly and validation.

Indexed as

MetagenomeAlgorithmsComputational BiologyDatabases, GeneticHigh-Throughput Nucleotide SequencingMetagenomicsMicrobiotaSoftwareassembly validationmetagenomic assemblymetagenomicsmicrobiomevariant discovery

Identifiers

PMID28968737
PMCPMC6781575

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.