Evidence map›Paper›PMID 32241255›Full record

ArticleBMC genomics2020

EpiMOLAS: an intuitive web-based framework for genome-wide DNA methylation analysis.

Sheng-Yao Su, I-Hsuan Lu, Wen-Chih Cheng, Wei-Chun Chung, Pao-Yang Chen, Jan-Ming Ho, Shu-Hwa Chen, Chung-Yen Lin

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 97% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Methods in DNA methylation array dataset analysis: A review.Computational and structural biotechnology journal · 2024
    Review
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

8 authors at 4 institutions in 1 country.

Sheng-Yao SuTaiwan International Graduate Program (TIGP) on Bioinformatics, Academia Sinica, Taipei, Taiwan.
I-Hsuan LuInstitute of Information Science, Academia Sinica, Taipei, Taiwan.
Wen-Chih ChengInstitute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan.
Wei-Chun ChungInstitute of Information Science, Academia Sinica, Taipei, Taiwan.
Pao-Yang ChenInstitute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan.
Jan-Ming HoInstitute of Information Science, Academia Sinica, Taipei, Taiwan.
Shu-Hwa ChenTMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei, Taiwan. sophia0715@tmu.edu.tw.
Chung-Yen LinInstitute of Information Science, Academia Sinica, Taipei, Taiwan. cylin@iis.sinica.edu.tw.
Institute of Information Science, Academia Sinica · TWNational Health Research Institutes · TWInstitute of Plant and Microbial Biology, Academia Sinica · TWTaipei Medical University · TW

Funding

Institute of Information Science Academia Sinica flagship programInstitute of Information Science, Academia Sinica flagship programMinistry of Science and Technology, Taiwan MOST108-2314-B-001-002Ministry of Science and Technology, Taiwan MOST108-2321-B-038-003Ministry of Science and Technology, Taiwan (TW) MOST107-2321-B-002-057Ministry of Science and Technology, Taiwan (TW) MOST108-2321-B-037-001
6 · The paper itself

Abstract

backgroundDNA methylation is a crucial epigenomic mechanism in various biological processes. Using whole-genome bisulfite sequencing (WGBS) technology, methylated cytosine sites can be revealed at the single nucleotide level. However, the WGBS data analysis process is usually complicated and challenging.

resultsTo alleviate the associated difficulties, we integrated the WGBS data processing steps and downstream analysis into a two-phase approach. First, we set up the required tools in Galaxy and developed workflows to calculate the methylation level from raw WGBS data and generate a methylation status summary, the mtable. This computation environment is wrapped into the Docker container image DocMethyl, which allows users to rapidly deploy an executable environment without tedious software installation and library dependency problems. Next, the mtable files were uploaded to the web server EpiMOLAS_web to link with the gene annotation databases that enable rapid data retrieval and analyses.

conclusionTo our knowledge, the EpiMOLAS framework, consisting of DocMethyl and EpiMOLAS_web, is the first approach to include containerization technology and a web-based system for WGBS data analysis from raw data processing to downstream analysis. EpiMOLAS will help users cope with their WGBS data and also conduct reproducible analyses of publicly available data, thereby gaining insights into the mechanisms underlying complex biological phenomenon. The Galaxy Docker image DocMethyl is available at https://hub.docker.com/r/lsbnb/docmethyl/. EpiMOLAS_web is publicly accessible at http://symbiosis.iis.sinica.edu.tw/epimolas/.

Indexed as

Computational BiologyCpG IslandsDNA MethylationGenome, HumanHumansInternetSoftwareWhole Genome SequencingDNA methylation data analysisDockerGalaxy platformWGBS pipeline

Identifiers

PMID32241255
PMCPMC7114791
OpenAlexW3014890926

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.