Evidence map›Paper›PMID 34570235›Full record

ArticleNucleic acids research2022

scMethBank: a database for single-cell whole genome DNA methylation maps.

Wenting Zong, Hongen Kang, Zhuang Xiong, Yingke Ma, Tong Jin, Zheng Gong, Lizhi Yi, Mochen Zhang, Song Wu, Guoliang Wang and 2 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  16. Databases and prospects of dynamic gene regulation in eukaryotes: A mini review.Computational and structural biotechnology journal · 2023
    Review
  17. Review
  18. 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

12 authors.

Wenting ZongNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0003-1834-9684
Hongen KangNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Zhuang XiongNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Yingke MaNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Tong JinNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Zheng GongNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0001-7285-2630
Lizhi YiNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Mochen ZhangNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Song WuNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Guoliang WangNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Yiming BaoNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Rujiao LiNational Genomics Data Center & CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell bisulfite sequencing methods are widely used to assess epigenomic heterogeneity in cell states. Over the past few years, large amounts of data have been generated and facilitated deeper understanding of the epigenetic regulation of many key biological processes including early embryonic development, cell differentiation and tumor progression. It is an urgent need to build a functional resource platform with the massive amount of data. Here, we present scMethBank, the first open access and comprehensive database dedicated to the collection, integration, analysis and visualization of single-cell DNA methylation data and metadata. Current release of scMethBank includes processed single-cell bisulfite sequencing data and curated metadata of 8328 samples derived from 15 public single-cell datasets, involving two species (human and mouse), 29 cell types and two diseases. In summary, scMethBank aims to assist researchers who are interested in cell heterogeneity to explore and utilize whole genome methylation data at single-cell level by providing browse, search, visualization, download functions and user-friendly online tools. The database is accessible at: https://ngdc.cncb.ac.cn/methbank/scm/.

Indexed as

Databases, GeneticDNA MethylationEpigenesis, GeneticGenomeSoftwareAnimalsChromosome MappingDatasets as TopicHumansInternetMetadataMiceMolecular Sequence AnnotationSingle-Cell AnalysisWhole Genome Sequencing

Identifiers

PMID34570235
PMCPMC8728155

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.