Evidence map›Paper›PMID 30365027›Full record

ArticleNucleic acids research2019

gcMeta: a Global Catalogue of Metagenomics platform to support the archiving, standardization and analysis of microbiome data.

Wenyu Shi, Heyuan Qi, Qinglan Sun, Guomei Fan, Shuangjiang Liu, Jun Wang, Baoli Zhu, Hongwei Liu, Fangqing Zhao, Xiaochen Wang and 6 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2019. 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
–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

48 citing papers in PubMed.

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  12. The African Human Microbiome Portal: a public web portal of curated metagenomic metadata.Database : the journal of biological databases and curation · 2024
    Article
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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

16 authors.

Wenyu ShiMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Heyuan QiMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Qinglan SunMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Guomei FanMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Shuangjiang LiuMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Jun WangCAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Science, Beijing 100101, China.
Baoli ZhuCAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Science, Beijing 100101, China.
Hongwei LiuState Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Science, Beijing 100101, China.
Fangqing ZhaoComputational Genomics Lab, Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.
Xiaochen WangMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Xiaoxuan HuMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Wei LiMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Jia LiuInternet of Things Information Technology and Application Laboratory, Computer Network Information Center, Chinese Academy of Sciences. Beijing 100101, China.
Ye TianInternet of Things Information Technology and Application Laboratory, Computer Network Information Center, Chinese Academy of Sciences. Beijing 100101, China.
Linhuan WuMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
Juncai MaMicrobial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Meta-omics approaches have been increasingly used to study the structure and function of the microbial communities. A variety of large-scale collaborative projects are being conducted to encompass samples from diverse environments and habitats. This change has resulted in enormous demands for long-term data maintenance and capacity for data analysis. The Global Catalogue of Metagenomics (gcMeta) is a part of the 'Chinese Academy of Sciences Initiative of Microbiome (CAS-CMI)', which focuses on studying the human and environmental microbiome, establishing depositories of samples, strains and data, as well as promoting international collaboration. To accommodate and rationally organize massive datasets derived from several thousands of human and environmental microbiome samples, gcMeta features a database management system for archiving and publishing data in a standardized way. Another main feature is the integration of more than ninety web-based data analysis tools and workflows through a Docker platform which enables data analysis by using various operating systems. This platform has been rapidly expanding, and now hosts data from the CAS-CMI and a number of other ongoing research projects. In conclusion, this platform presents a powerful and user-friendly service to support worldwide collaborative efforts in the field of meta-omics research. This platform is freely accessible at https://gcmeta.wdcm.org/.

Indexed as

Databases, GeneticMetagenomeMicrobiotaSoftwareMetagenomicsReference Standards

Identifiers

PMID30365027
PMCPMC6324004

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.