ArticleBioinformatics (Oxford, England)2018
EWAS: epigenome-wide association study software 2.0.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Multiome-wide Association Studies: Novel Approaches for Understanding Diseases.Genomics, proteomics & bioinformatics · 2024Review
- DNA methylation variations underlie lettuce domestication and divergence.Genome biology · 2024Article
- Methylation haplotypes of the insulin gene promoter in children and adolescents with type 1 diabetes: Can a dimensionality reduction approach predict the disease?Experimental and therapeutic medicine · 2023Article
- Asymmetric variation in DNA methylation during domestication and de-domestication of rice.The Plant cell · 2023Article
- RABC: Rheumatoid Arthritis Bioinformatics Center.Nucleic acids research · 2023Article
- Identification of novel meQTLs strongly associated with rheumatoid arthritis by large-scale epigenome-wide analysis.FEBS open bio · 2022Article
- Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm.Journal of personalized medicine · 2022Review
- EWAS Open Platform: integrated data, knowledge and toolkit for epigenome-wide association study.Nucleic acids research · 2022Article
- Ten Years of EWAS.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Review
- Mergeomics 2.0: a web server for multi-omics data integration to elucidate disease networks and predict therapeutics.Nucleic acids research · 2021Article
- Article
- Mining the Selective Remodeling of DNA Methylation in Promoter Regions to Identify Robust Gene-Level Associations With Phenotype.Frontiers in molecular biosciences · 2021Article
- Article
- Imputing missing RNA-sequencing data from DNA methylation by using a transfer learning-based neural network.GigaScience · 2020Article
- Genome-wide association studies of severe P. falciparum malaria susceptibility: progress, pitfalls and prospects.BMC medical genomics · 2019Review
- EWASdb: epigenome-wide association study database.Nucleic acids research · 2019Article
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.