QDMR:Quantitative Differentially Methylated Region
  Summary Last Update: 04/20/2017
Welcome to QDMR!
QDMR (Quantitative Differentially Methylated Regions) is a quantitative approach to quantify methylation difference and identify DMRs from genome-wide methylation profiles by adapting Shannon entropy. The platform-free and species-free nature of QDMR makes it potentially applicable to various methylation data. This approach provides an effective tool for the high-throughput identification of the functional regions involved in epigenetic regulation.
The current version of QDMR provide users three both online platform and standalone software for methylation data. And the command line version of QDMR is also launched recently to facilitate the analysis of massive methylation data.
QDMR works from the imported methylation data across a number of samples. It performs all of the steps in following the workflow in Tutorial, including Import Data, Quantify Difference, Identify DMRs, Measure Specificity and Export All Results. Its graphical tools also allow the user to manually inspect the raw methylation levels across samples any time.

QDMR is also available at http://fame.edbc.org/qdmr/ New!


  Getting Started   What's New >>

Learn to use QDMR in 10 minutes:
Learn hands-on with the Quick Start tutorial

10/17/2012: The command line version of QDMR 1.0 is officially launched now. (Download, Tutorial) New!
Run analysis now at QDMR server
Use QDMR to run analysis directly on your web browser.
10/16/2012: The QDMR forum can be used to exchange about QDMR usage now at Google Group.. New!
Download QDMR
Use QDMR locally on Windows, Mac OS X, Linux, or Solaris.
  10/16/2012: QDMR provides Frequently Asked Questions (FAQ) pages for users.. New!

Please cite QDMR as you use it for your work: [Abstract] [Full Text] [PDF]
Yan Zhang, Hongbo Liu, Jie Lv, Xue Xiao, Jiang Zhu, Xiaojuan Liu, Jianzhong Su, Xia Li, Qiong Wu, Fang Wang and Ying Cui (2011) QDMR: a quantitative method for identification of differentially methylated regions by entropy. Nucleic Acids Res, 39, e58.

  SMART: New tool for bisulfite sequencing data analysis New!

SMART is a newly developed tool for deep analysis of DNA methylation data detected by bisulfite sequencing platforms. This tool is focused on three main functions including de novo identification of DMRs by genome segmentation, identification of DMRs from predifined regions of interest, and identification of differentially methylated CpG sites.

SMART is available at http://fame.edbc.org/smart/.

Reference: Hongbo Liu et al. Systematic identification and annotation of human methylation marks based on bisulfite sequencing methylomes reveals distinct roles of cell type-specific hypomethylation in the regulation of cell identity genes Nucleic Acids Res: 2016 ,44(1) ,75-94.

Our Lab:Group of computational epigenetic research
CopyRight © Group of Computational Epigenetic Research
College of Bioinformatics Science and Technology, Harbin Medical University, China
Our college website (Chinese Version)
Recommended Browser: Mozilla Firefox (1024*768)
free counters