EpiDISH statistics

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Citations per year

Number of citations per year for the bioinformatics software tool EpiDISH
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Tool usage distribution map

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

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EpiDISH specifications

Information


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

Subtool


  • CellDMC

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Documentation


Maintainer


  • person_outline Andrew Teschendorff

Publications for Epigenetic Dissection of Intra-Sample Heterogeneity

EpiDISH citations

 (2)
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Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits

2018
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. […]

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The epigenomic basis of common diseases

2017
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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