Your browser doesn't support javascript.
loading
EWAS: epigenome-wide association study software 2.0.
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.
Afiliação
  • Xu J; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Zhao L; Training Center for Students Innovation and Entrepreneurship Education, Harbin Medical University, Harbin, China.
  • Liu D; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Hu S; Training Center for Students Innovation and Entrepreneurship Education, Harbin Medical University, Harbin, China.
  • Song X; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Li J; Training Center for Students Innovation and Entrepreneurship Education, Harbin Medical University, Harbin, China.
  • Lv H; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Duan L; Training Center for Students Innovation and Entrepreneurship Education, Harbin Medical University, Harbin, China.
  • Zhang M; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Jiang Q; Training Center for Students Innovation and Entrepreneurship Education, Harbin Medical University, Harbin, China.
  • Liu G; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Jin S; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Liao M; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Zhang M; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Feng R; Center for Bioinformatics, School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
  • Kong F; Center for Bioinformatics, School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
  • Xu L; Department of Mathematics, Harbin Institute of Technology, Harbin, China.
  • Jiang Y; College of Life Science, Northwest A&F University, Yangling, Shaanxi, China.
Bioinformatics ; 34(15): 2657-2658, 2018 08 01.
Article em En | MEDLINE | ID: mdl-29566144
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article