Evidence map›Paper›PMID 31749830›Full record

ArticleFrontiers in genetics2019

Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes.

Jiarong Guo, John F Quensen, Yanni Sun, Qiong Wang, C Titus Brown, James R Cole, James M Tiedje

Abstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  6. Review
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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.

Jiarong GuoCenter for Microbial Ecology, Michigan State University, East Lansing, MI, United States.
John F QuensenCenter for Microbial Ecology, Michigan State University, East Lansing, MI, United States.
Yanni SunDepartment of Electronical Engineering, City University of Hong Kong, Kowloon, Hong Kong.
Qiong WangCenter for Microbial Ecology, Michigan State University, East Lansing, MI, United States.
C Titus BrownDepartment of Population Health and Reproduction, University of California, Davis, Davis, CA, United States.
James R ColeCenter for Microbial Ecology, Michigan State University, East Lansing, MI, United States.
James M TiedjeCenter for Microbial Ecology, Michigan State University, East Lansing, MI, United States.

Funding

VOLATILE ORGANIC CONTAMINANTS--QUANTIFYING THEIR MOVEMENT IN THE UNSATURATED ZONEP42ES004911 · NIEHS · MICHIGAN STATE UNIVERSITY · PI Brian P. Johnson · 1989 to 2026
$64.9M
NIEHS NIH HHS P42 ES004911
6 · The paper itself

Abstract

Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (

Indexed as

gene-centric assemblygene-targeted assemblyMegaGTAmicrobial ecologyXander

Identifiers

PMID31749830
PMCPMC6843070

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LicenceCC BY
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Registered trials

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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.