EpiDISH statistics

info info

Citations per year


Popular tool citations

chevron_left Differentially methylated region detection EWAS chevron_right

Tool usage distribution map

Tool usage distribution map
info info

Associated diseases

Associated diseases
Want to access the full stats & trends on this tool?

EpiDISH specifications


Unique identifier OMICS_15070
Name EpiDISH
Alternative name Epigenetic Dissection of Intra-Sample Heterogeneity
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 1.0
Stability Stable
Maintained Yes


  • CellDMC




No version available



  • person_outline Andrew Teschendorff

Publications for Epigenetic Dissection of Intra-Sample Heterogeneity

EpiDISH citations


Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits

PMCID: 5802460
PMID: 29382824
DOI: 10.1038/s41398-017-0070-x

[…] principal component analysis axes., cell type proportion estimates (cd4 t cells, cd8 t cells, natural killers, granulocytes, monocytes, and lymphocytes b) were obtained for each sample using the epidish-cibersort approach. in each testing dataset, we compared estimeth model performance before and after further linear regression adjustment of dnam for the estimated cell type proportions., dna […]


The epigenomic basis of common diseases

Clin Epigenetics
PMCID: 5270348
PMID: 28149333
DOI: 10.1186/s13148-017-0313-y

[…] several bioinformatic tools for ewas interpretation such as eforge (http://eforge.cs.ucl.ac.uk), which identifies tissue or cell-type specific signals from illumina 450k methylation array data [], epidish (freely available from https://github.com/sjczheng/epidish), which can be used for epigenetic dissection of heterogeneity within a sample, and coralina (comprehensive guide rna library […]

Want to access the full list of citations?
EpiDISH institution(s)
CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China; Department of Women’s Cancer, University College London, London, UK; Statistical Cancer Genomics, Paul O’Gorman Building, UCL Cancer Institute, University College London, London, UK; Medical Genomics, Paul O’Gorman Building, UCL Cancer Institute, University College London, London, UK; University of Chinese Academy of Sciences, Beijing, China
EpiDISH funding source(s)
This work was supported by a Royal Society Newton Advanced Fellowship (AET & SB), NAF project number: 522438, NAF award number: 164914.

EpiDISH reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review EpiDISH