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


Journal

BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258

Informations de publication

Date de publication:
02 Apr 2020
Historique:
received: 02 11 2019
accepted: 16 12 2019
entrez: 4 4 2020
pubmed: 4 4 2020
medline: 24 10 2020
Statut: epublish

Résumé

DNA 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. To 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. To 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/.

Sections du résumé

BACKGROUND BACKGROUND
DNA 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.
RESULTS RESULTS
To 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.
CONCLUSION CONCLUSIONS
To 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/.

Identifiants

pubmed: 32241255
doi: 10.1186/s12864-019-6404-8
pii: 10.1186/s12864-019-6404-8
pmc: PMC7114791
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

163

Subventions

Organisme : Ministry of Science and Technology, Taiwan (TW)
ID : MOST107-2321-B-002-057
Organisme : Ministry of Science and Technology, Taiwan (TW)
ID : MOST108-2321-B-037-001
Organisme : Institute of Information Science, Academia Sinica
ID : flagship program
Organisme : Institute of Information Science Academia Sinica
ID : flagship program
Organisme : Ministry of Science and Technology, Taiwan
ID : MOST108-2314-B-001-002
Organisme : Ministry of Science and Technology, Taiwan
ID : MOST108-2321-B-038-003

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Auteurs

Sheng-Yao Su (SY)

Taiwan International Graduate Program (TIGP) on Bioinformatics, Academia Sinica, Taipei, Taiwan.
Institute of Information Science, Academia Sinica, Taipei, Taiwan.
Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.

I-Hsuan Lu (IH)

Institute of Information Science, Academia Sinica, Taipei, Taiwan.

Wen-Chih Cheng (WC)

Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan.

Wei-Chun Chung (WC)

Institute of Information Science, Academia Sinica, Taipei, Taiwan.

Pao-Yang Chen (PY)

Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan.

Jan-Ming Ho (JM)

Institute of Information Science, Academia Sinica, Taipei, Taiwan.

Shu-Hwa Chen (SH)

TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei, Taiwan. sophia0715@tmu.edu.tw.

Chung-Yen Lin (CY)

Institute of Information Science, Academia Sinica, Taipei, Taiwan. cylin@iis.sinica.edu.tw.
Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan. cylin@iis.sinica.edu.tw.
Institute of Fisheries Science, College of Life Science, National Taiwan University, Taipei, Taiwan. cylin@iis.sinica.edu.tw.

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Classifications MeSH