Chapter title |
Tools and Strategies for Analysis of Genome-Wide and Gene-Specific DNA Methylation Patterns
|
---|---|
Chapter number | 15 |
Book title |
Oral Biology
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6685-1_15 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6683-7, 978-1-4939-6685-1
|
Authors |
Aniruddha Chatterjee, Euan J. Rodger, Ian M. Morison, Michael R. Eccles, Peter A. Stockwell, Chatterjee, Aniruddha, Rodger, Euan J., Morison, Ian M., Eccles, Michael R., Stockwell, Peter A. |
Editors |
Gregory J. Seymour, Mary P. Cullinan, Nicholas C.K. Heng |
Abstract |
DNA methylation is a stable epigenetic mechanism that has important roles in the normal function of a cell and therefore also in disease etiology. Accurate measurements of normal and altered DNA methylation patterns are important to understand its role in regulating gene expression and cell phenotype. Remarkable progress has been made over the last decade in developing methodologies to investigate DNA methylation. The availability of next-generation sequencing has enabled the profiling of methylation marks at an unprecedented scale. Several methods that were previously used to profile locus-specific methylation have now been upgraded to a genome-wide scale using high-throughput sequencing or array platforms. However, because there are so many techniques available, researchers are faced with the challenge of assessing the potential merits or limitations of each technique and selecting the appropriate method for their analysis. In this review we discuss the strengths and weaknesses of genome-wide and gene-specific analysis tools for interrogating DNA methylation. We particularly focus on the design and analysis strategies involved. This review will provide a guideline for selecting the appropriate methods and tools for large-scale and locus-specific DNA methylation analysis. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
New Zealand | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 78 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 14 | 18% |
Researcher | 10 | 13% |
Unspecified | 6 | 8% |
Student > Bachelor | 6 | 8% |
Student > Doctoral Student | 4 | 5% |
Other | 14 | 18% |
Unknown | 24 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 22 | 28% |
Agricultural and Biological Sciences | 7 | 9% |
Unspecified | 6 | 8% |
Medicine and Dentistry | 3 | 4% |
Computer Science | 2 | 3% |
Other | 7 | 9% |
Unknown | 31 | 40% |