EpiDISH statistics

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Citations per year

Number of citations per year for the bioinformatics software tool EpiDISH

Tool usage distribution map

This map represents all the scientific publications referring to EpiDISH per scientific context
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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

[…] 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. […]


The epigenomic basis of common diseases

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

[…] ed 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 generat […]

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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.

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