Abstract
Motivation: DNA methylation has been used to identify functional changes at transcriptional enhancers and other cis-regulatory modules (CRMs) in tumors and other disease tissues. Our R/Bioconductor package ELMER (Enhancer Linking by Methylation/Expression Relationships) provides a systematic approach that reconstructs altered gene regulatory networks (GRNs) by combining enhancer methylation and gene expression data derived from the same sample set. Results: We present a completely revised version 2 of ELMER that provides numerous new features including an optional web-based interface and a new Supervised Analysis mode to use pre-defined sample groupings. We show that Supervised mode significantly increases statistical power and identifies additional GRNs and associated Master Regulators, such as SOX11 and KLF5 in Basal-like breast cancer. Availability and implementation: ELMER v.2 is available as an R/Bioconductor package at http://bioconductor.org/packages/ELMER/. Supplementary information: Supplementary data are available at Bioinformatics online.
| Original language | English |
|---|---|
| Article number | bty902 |
| Pages (from-to) | 1974-1977 |
| Number of pages | 4 |
| Journal | Bioinformatics |
| Volume | 35 |
| Issue number | 11 |
| DOIs | |
| State | Published - 1 Jun 2019 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2018 The Author(s) 2018. Published by Oxford University Press.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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