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Nucleic acids research
01 07, 2022;50 (D1): D1208-D1215.

DiseaseMeth version 3.0: a major expansion and update of the human disease methylation database.

Jie Xing, Ruiyang Zhai, Cong Wang, Honghao Liu, Jiaqi Zeng, Dianshuang Zhou, Mengyan Zhang, Liru Wang, Qiong Wu, Yue Gu, Yan Zhang
Author Information
  1. Jie Xing: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  2. Ruiyang Zhai: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  3. Cong Wang: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  4. Honghao Liu: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  5. Jiaqi Zeng: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  6. Dianshuang Zhou: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  7. Mengyan Zhang: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  8. Liru Wang: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  9. Qiong Wu: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  10. Yue Gu: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China.
  11. Yan Zhang: School of Life Science and Technology, Computational Biology Research Center, Harbin Institute of Technology, Harbin 150001, China. ORCID
PMID: 34792145 DOI: 10.1093/nar/gkab1088

Abstract

DNA methylation has a growing potential for use as a biomarker because of its involvement in disease. DNA methylation data have also substantially grown in volume during the past 5 years. To facilitate access to these fragmented data, we proposed DiseaseMeth version 3.0 based on DiseaseMeth version 2.0, in which the number of diseases including increased from 88 to 162 and High-throughput profiles samples increased from 32 701 to 49 949. Experimentally confirmed associations added 448 pairs obtained by manual literature mining from 1472 papers in PubMed. The search, analyze and tools sections were updated to increase performance. In particular, the FunctionSearch now provides for the functional enrichment of genes from localized GO and KEGG annotation. We have also developed a unified analysis pipeline for identifying differentially DNA methylated genes (DMGs) from the original data stored in the database. 22 718 DMGs were found in 99 diseases. These DMGs offer application in disease evaluation using two self-developed online tools, Methylation Disease Correlation and Cancer Prognosis & Co-Methylation. All query results can be downloaded and can also be displayed through a box plot, heatmap or network module according to whichever search section is used. DiseaseMeth version 3.0 is freely available at http://diseasemeth.edbc.org/.

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MeSH Term

Biomarkers, Tumor
DNA Methylation
Databases, Factual
Gene Expression Profiling
Genetic Diseases, Inborn
Humans
Neoplasms
PubMed

Chemicals

Biomarkers, Tumor
Journal Article Research Support, Non-U.S. Gov't

Links to CNCB-NGDC Resources

Database Commons: DBC000555 (DiseaseMeth)

Word Cloud

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