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deepEA: a containerized web server for interactive analysis of epitranscriptome sequencing data

Home Page: https://cma2015.github.io/deepEA

HTML 98.91% CSS 0.24% JavaScript 0.07% Shell 0.04% R 0.62% Python 0.09% Dockerfile 0.03%
epitranscriptome galaxy ngs-analysis machine-learning

deepea's Introduction

Introduction

  • 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.

How to use deepEA

How to cite 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

How to access help

Change log

  • 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

deepea's People

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