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CpG Islands

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Cover of 'CpG Islands'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 CpG Islands: A Historical Perspective
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    Chapter 2 Biochemical Identification of Nonmethylated DNA by BioCAP-Seq
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    Chapter 3 Prediction of CpG Islands as an Intrinsic Clustering Property Found in Many Eukaryotic DNA Sequences and Its Relation to DNA Methylation
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    Chapter 4 CpG Islands in Cancer: Heads, Tails, and Sides
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    Chapter 5 Infinium DNA Methylation Microarrays on Formalin-Fixed, Paraffin-Embedded Samples
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    Chapter 6 The Use of Methylation-Sensitive Multiplex Ligation-Dependent Probe Amplification for Quantification of Imprinted Methylation
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    Chapter 7 The Pancancer DNA Methylation Trackhub: A Window to The Cancer Genome Atlas Epigenomics Data
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    Chapter 8 Methylation-Sensitive Amplification Length Polymorphism (MS-AFLP) Microarrays for Epigenetic Analysis of Human Genomes
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    Chapter 9 Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells
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    Chapter 10 Experimental Design and Bioinformatic Analysis of DNA Methylation Data
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    Chapter 11 Assay for Transposase Accessible Chromatin (ATAC-Seq) to Chart the Open Chromatin Landscape of Human Pancreatic Islets
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    Chapter 12 Defining Regulatory Elements in the Human Genome Using Nucleosome Occupancy and Methylome Sequencing (NOMe-Seq)
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    Chapter 13 Genome-Wide Mapping of Protein–DNA Interactions on Nascent Chromatin
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    Chapter 14 Analysis of Chromatin Interactions Mediated by Specific Architectural Proteins in Drosophila Cells
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    Chapter 15 High-Throughput Single-Cell RNA Sequencing and Data Analysis
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    Chapter 16 Functional Insulator Scanning of CpG Islands to Identify Regulatory Regions of Promoters Using CRISPR
  18. Altmetric Badge
    Chapter 17 An Application-Directed, Versatile DNA FISH Platform for Research and Diagnostics
Attention for Chapter 7: The Pancancer DNA Methylation Trackhub: A Window to The Cancer Genome Atlas Epigenomics Data
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Chapter title
The Pancancer DNA Methylation Trackhub: A Window to The Cancer Genome Atlas Epigenomics Data
Chapter number 7
Book title
CpG Islands
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7768-0_7
Pubmed ID
Book ISBNs
978-1-4939-7767-3, 978-1-4939-7768-0
Authors

Izaskun Mallona, Alberto Sierco, Miguel A. Peinado

Abstract

The Cancer Genome Atlas (TCGA) epigenome data includes the DNA methylation status of tumor and normal tissues of large cohorts for dozens of cancer types. Due to the moderately large data sizes, retrieving and analyzing them requires basic programming skills. Simple data browsing (e.g., candidate gene search) is hampered by the scarcity of easy-to-use data browsers addressed to the broad community of biomedical researchers. We propose a new visualization method depicting the overall DNA methylation status at each TCGA cohort while emphasizing its heterogeneity, thus facilitating the evaluation of the cohort variability and the normal versus tumor differences. Implemented as a trackhub integrated to the University of California Santa Cruz (UCSC) genome browser, it can be easily added to any genome-wide annotation layer.To exemplify the trackhub usage we evaluate local DNA methylation boundaries, the aberrant DNA methylation of a CpG island located at the estrogen receptor 1 (ESR1) in breast and colon cancer, and the hypermethylation of the Homeobox HOXA gene cluster and the EN1 gene in multiple cancer types. The DNA methylation pancancer trackhub is freely available at http://maplab.cat/tcga_450k_trackhub .

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 29%
Researcher 2 14%
Student > Doctoral Student 1 7%
Other 1 7%
Unspecified 1 7%
Other 1 7%
Unknown 4 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 29%
Computer Science 3 21%
Unspecified 1 7%
Medicine and Dentistry 1 7%
Design 1 7%
Other 0 0%
Unknown 4 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 April 2018.
All research outputs
#11,337,139
of 12,745,229 outputs
Outputs from Methods in molecular biology
#5,939
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Outputs of similar age
#237,564
of 273,184 outputs
Outputs of similar age from Methods in molecular biology
#6
of 7 outputs
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