The EWAS Project

EWAS is a Java package for epigenome-wide association study (EWAS).

EWAS can identify the association between DNA methylation levels and complex diseases.

The more functions can be found in our software as we will develop our software in the future from the following aspects.

  1. epigenome-wide association study for beta value (completed)

  2. epigenome-wide association study for SMP ( single methylation polymorphisms, completed)
  3. epigenome-wide association study for meplotype (methylation haplotype,completed)
  4. epigenome-wide association study for methylecomtype (completed)

  5. database for epigenome-wide association study  (completed)
  6. epigenome-wide association study for gene region (upcoming)
  7. epigenome-wide association study for KEGG pathway (upcoming)
  8. epigenome-wide association study for GO catogories (upcoming)
  9. epigenome-wide association study for network (upcoming)

10. epigenome-wide association study for interacting with genetic marker (upcoming)

11. epigenome-wide association study for gene expression (upcoming)

12. epigenome-wide association study for RNA modification (upcoming)

13. epigenome-wide association study for histone modification (upcoming)

Work in progress

EWAS v2.0 download

What's new in EWAS v2.0 :

• Carry out linear regression analysis (continuous phenotype).
• Calculate the Pearson's correlation coefficients (continuous phenotype).
• Carry out logistic regression analysis(case/control or binomial phenotype).
• Convert DNA methlytion beta-value to SMP menoypte (MM MU or UU).
• Chisq-square test for SMP meplotypes 2 (phenotype)*2 ( M vs. U) table.
• Identify the type of SMP allele association for each DNA methylation loci.
• Calculate the MAF and Hady-Weinberg pvalue for each DNA methylation loci.
• Give a summary statistic for each DNA methylation loci.
• Identify the epigenome wide DNA methylation haplotype (meplotype) blocks.
• Estimate the meplotype frequency.
• Carry out epigenome wide meplotype association study.
• Carry out epigenome wide meta-analysis.

How to Cite EWAS ?

EWAS project needs your support!

Please cite the following paper when you use EWAS. Most analysis method can be found in this paper.

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1. Di liu, Linna Zhao, Zhaoyang Wang, Xu Zhou, Xiuzhao Fan, Yong Li,Jing Xu, Simeng Hu, Miaomiao Niu, Xiuling Song, Ying Li, Lijiao Zuo, Changgui Lei, Meng Zhang, Guoping Tang, Min Huang, Nan Zhang, Lian Duan, Hongchao Lv, Mingming Zhang, Jin Li, Liangde Xu, Fanwu Kong, Rennan Feng and Yongshuai Jiang. EWASdb: epigenome-wide association study database.

Nucleic Acids Res. 2018 Oct 13.

[Abstract]     [PDF]     [PubMed entry]

 

2. Jing Xu, Linna Zhao, Di Liu, Simeng Hu1, Xiuling Song, Jin Li, Hongchao Lv, Lian Duan, Mingming Zhang, Qinghua Jiang, Guiyou Liu, Shuilin Jin, Mingzhi Liao, Meng Zhang, Rennan Feng, Fanwu Kong, Liangde Xu & Yongshuai Jiang. EWAS: epigenome-wide association study software 2.0.

Bioinformatics. 2018 Aug 1.

[Abstract]     [PDF]     [PubMed entry]

 

3. Linna Zhao, Di Liu, Jing Xu, Zhaoyang Wang, Yang Chen,Changgui Lei, Ying Li, Guiyou Liu and Yongshuai Jiang. The framework for population epigenetic study. Brief Bioinform. 2016 Oct 19. pii: bbw098.

[Abstract]     [PDF]     [PubMed entry]