Evidence map›Paper›PMID 26951112›Full record

ReviewMicrobiome2016

Recovering complete and draft population genomes from metagenome datasets.

Naseer Sangwan, Fangfang Xia, Jack A Gilbert

Abstract readReview
In one paragraph

Review in Microbiome, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 135 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
135citing 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

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

  1. Pooled it
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  4. Computational Microbial and Viral Ecology Analysis.Methods in molecular biology (Clifton, N.J.) · 2026
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75 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.

Naseer SangwanBiosciences Division (BIO), Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL, 60439, USA. nikki1018sangwan@gmail.com.
Fangfang XiaComputing, Environment and Life Sciences, Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL, 60439, USA. fangfang@anl.gov.
Jack A GilbertBiosciences Division (BIO), Argonne National Laboratory, 9700 South Cass Avenue, Argonne, IL, 60439, USA. gilbertjack@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assembly of metagenomic sequence data into microbial genomes is of fundamental value to improving our understanding of microbial ecology and metabolism by elucidating the functional potential of hard-to-culture microorganisms. Here, we provide a synthesis of available methods to bin metagenomic contigs into species-level groups and highlight how genetic diversity, sequencing depth, and coverage influence binning success. Despite the computational cost on application to deeply sequenced complex metagenomes (e.g., soil), covarying patterns of contig coverage across multiple datasets significantly improves the binning process. We also discuss and compare current genome validation methods and reveal how these methods tackle the problem of chimeric genome bins i.e., sequences from multiple species. Finally, we explore how population genome assembly can be used to uncover biogeographic trends and to characterize the effect of in situ functional constraints on the genome-wide evolution.

Indexed as

Genome, MicrobialMetagenomeContig MappingDatasets as TopicMetagenomicsSequence Analysis, DNA

Identifiers

PMID26951112
PMCPMC4782286

What OpenQuestion holds

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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.