Evidence map›Paper›PMID 31584095›Full record

ArticleNucleic acids research2020

EWAS Data Hub: a resource of DNA methylation array data and metadata.

Zhuang Xiong, Mengwei Li, Fei Yang, Yingke Ma, Jian Sang, Rujiao Li, Zhaohua Li, Zhang Zhang, Yiming Bao

Abstract read
In one paragraph

Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing 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

76 citing papers in PubMed.

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  12. A Residual Approach to Estimate Biological Age from Gompertz Modeling.medRxiv : the preprint server for health sciences · 2025
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  17. Translational cancer research · 2025
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16 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

9 authors.

Zhuang XiongNational Genomics Data Center, Beijing 100101, China.
Mengwei LiNational Genomics Data Center, Beijing 100101, China.
Fei YangNational Genomics Data Center, Beijing 100101, China.
Yingke MaNational Genomics Data Center, Beijing 100101, China.
Jian SangNational Genomics Data Center, Beijing 100101, China.
Rujiao LiNational Genomics Data Center, Beijing 100101, China.
Zhaohua LiNational Genomics Data Center, Beijing 100101, China.
Zhang ZhangNational Genomics Data Center, Beijing 100101, China.
Yiming BaoNational Genomics Data Center, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

Indexed as

Databases, GeneticEpigenesis, GeneticGenome-Wide Association StudyMetadataBiomarkersDNA MethylationEpigenomeHumansBiomarkers

Identifiers

PMID31584095
PMCPMC6943079

What OpenQuestion holds

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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.