Evidence map›Paper›PMID 32471342›Full record

ArticleBMC genomics2020

MethGET: web-based bioinformatics software for correlating genome-wide DNA methylation and gene expression.

Chin-Sheng Teng, Bing-Heng Wu, Ming-Ren Yen, Pao-Yang Chen

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
4.7field-weighted citation impact, top 4% of its field
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

20 citing papers in PubMed, 46 citations in OpenAlex.

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  18. MIAOME: Human microbiome affect the host epigenome.Computational and structural biotechnology journal · 2022
    Article
  19. Review
  20. Epigenomic and transcriptomic analyses reveal early activation of the HPG axis in in vitro-produced male dairy calves.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2021
    Article
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

4 authors at 3 institutions in 1 country.

Chin-Sheng TengInstitute of Plant and Microbial Biology, Academia Sinica, No. 128, Section 2, Academia Rd, Nangang District, Taipei City, 11529, Taiwan.
Bing-Heng WuInstitute of Plant and Microbial Biology, Academia Sinica, No. 128, Section 2, Academia Rd, Nangang District, Taipei City, 11529, Taiwan.
Ming-Ren YenInstitute of Plant and Microbial Biology, Academia Sinica, No. 128, Section 2, Academia Rd, Nangang District, Taipei City, 11529, Taiwan.
Pao-Yang ChenInstitute of Plant and Microbial Biology, Academia Sinica, No. 128, Section 2, Academia Rd, Nangang District, Taipei City, 11529, Taiwan. paoyang@gate.sinica.edu.tw.ORCID http://orcid.org/0000-0002-7402-3075
Institute of Plant and Microbial Biology, Academia Sinica · TWNational Taiwan University · TWNational Taiwan University of Science and Technology · TW

Funding

Ministry of Science and Technology MoST 106-2311-B-001 -035 -MY3Ministry of Science and Technology, Taiwan 108-2313-B-001 -013 -MY3Ministry of Science and Technology, Taiwan MOST 107-2813-C-001 -015 -B
6 · The paper itself

Abstract

backgroundDNA methylation is a major epigenetic modification involved in regulating gene expression. The effects of DNA methylation on gene expression differ by genomic location and vary across kingdoms, species and environmental conditions. To identify the functional regulatory roles of DNA methylation, the correlation between DNA methylation changes and alterations in gene expression is crucial. With the advance of next-generation sequencing, genome-wide methylation and gene expression profiling have become feasible. Current bioinformatics tools for investigating such correlation are designed to the assessment of DNA methylation at CG sites. The correlation of non-CG methylation and gene expression is very limited. Some bioinformatics databases allow correlation analysis, but they are limited to specific genomes such as that of humans and do not allow user-provided data.

resultsHere, we developed a bioinformatics web tool, MethGET (Methylation and Gene Expression Teller), that is specialized to analyse the association between genome-wide DNA methylation and gene expression. MethGET is the first web tool to which users can supply their own data from any genome. It is also the tool that correlates gene expression with CG, CHG, and CHH methylation based on whole-genome bisulfite sequencing data. MethGET not only reveals the correlation within an individual sample (single-methylome) but also performs comparisons between two groups of samples (multiple-methylomes). For single-methylome analyses, MethGET provides Pearson correlations and ordinal associations to investigate the relationship between DNA methylation and gene expression. It also groups genes with different gene expression levels to view the methylation distribution at specific genomic regions. Multiple-methylome analyses include comparative analyses and heatmap representations between two groups. These functions enable the detailed investigation of the role of DNA methylation in gene regulation. Additionally, we applied MethGET to rice regeneration data and discovered that CHH methylation in the gene body region may play a role in the tissue culture process, which demonstrates the capability of MethGET for use in epigenomic research.

conclusionsMethGET is a Python software that correlates DNA methylation and gene expression. Its web interface is publicly available at https://paoyang.ipmb.sinica.edu.tw/Software.html. The stand-alone version and source codes are available on GitHub at https://github.com/Jason-Teng/MethGET.

Indexed as

DNA MethylationGene Expression ProfilingInternetSoftwareGenomicsHumansBioinformaticsCorrelationDNA methylationEpigenomeGene expressionNext-generation sequencingWeb server

Identifiers

PMID32471342
PMCPMC7257144
OpenAlexW3030675781

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.