EWAS: epigenome-wide association study software 2.0

• Published in: Bioinformatics Vol. 34; no. 15; pp. 2657 - 2658
• Main Authors: Xu, Jing, Zhao, Linna, Liu, Di, Hu, Simeng, Song, Xiuling, Li, Jin, Lv, Hongchao, Duan, Lian, Zhang, Mingming, Jiang, Qinghua, Liu, Guiyou, Jin, Shuilin, Liao, Mingzhi, Zhang, Meng, Feng, Rennan, Kong, Fanwu, Xu, Liangde, Jiang, Yongshuai
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.08.2018
• Subjects: Applications Notes
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/bty163

Abstract Motivation With the development of biotechnology, DNA methylation data showed exponential growth. Epigenome-wide association study (EWAS) provide a systematic approach to uncovering epigenetic variants underlying common diseases/phenotypes. But the EWAS software has lagged behind compared with genome-wide association study (GWAS). To meet the requirements of users, we developed a convenient and useful software, EWAS2.0. Results EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our 'population epigenetic framework' and can perform: (i) epigenome-wide single marker association study; (ii) epigenome-wide methylation haplotype (meplotype) association study and (iii) epigenome-wide association meta-analysis. Users can use EWAS2.0 to execute chi-square test, t-test, linear regression analysis, logistic regression analysis, identify the association between epi-alleles, identify the methylation disequilibrium (MD) blocks, calculate the MD coefficient, the frequency of meplotype and Pearson's correlation coefficients and carry out meta-analysis and so on. Finally, we expect EWAS2.0 to become a popular software and be widely used in epigenome-wide associated studies in the future. Availability and implementation The EWAS software is freely available at http://www.ewas.org.cn or http://www.bioapp.org/ewas.