- deepEA is a convenient, freely available, web-based platform that is capable to support deep analysis of epitranscriptome sequencing data with several general and specific functionalities. Currently, deepEA consists of six modules: Data Preparation, Quality Control, Identification of RNA Modifications, Functional Annotation, Multi-omics Integrative Analysis and Prediction Analysis Based on Machine Learning.
- The deepEA demo server can be accessed via http://deepea.omicstudio.cloud.
- The deepEA project is hosted on https://cma2015.github.io/deepEA.
- The deepEA Docker image can be obtained from https://hub.docker.com/r/malab/deepea.
- Test data and tutorial of deepEA are presented at https://cma2015.github.io/deepEA
- Zhai J, Song J, Zhang T, Xie S, Ma C*. 2021. deepEA: a containerized web server for interactive analysis of epitranscriptome sequencing data. Plant Physiology, 185: 29-33
- Comments/suggestions/bugs/issues are welcome reported here or contact: Jingjing Zhai zhaijingjing603@gmail.com or Chuang Ma chuangma2006@gmail.com
- 2020.09 Add m6 sequencing data analysis pipeline in tutorial
- 2020.08 Release deepEA v1.0
- 2020.06 Update multi-omics integration
- 2020.06 Optimize feature encoding to perform parallel analysis
- 2020.04 fixed admin user bug
- 2019.11 we updated deepEA
- 2019.01 deepEA web server online
- 2018.05 we launched deepEA project