Jump to ContentJump to Main Navigation
Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics$
Users without a subscription are not able to see the full content.

Christine Sinoquet and Raphaël Mourad

Print publication date: 2014

Print ISBN-13: 9780198709022

Published to Oxford Scholarship Online: December 2014

DOI: 10.1093/acprof:oso/9780198709022.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 19 October 2021

Latent Variable Models for Analyzing DNA Methylation

Latent Variable Models for Analyzing DNA Methylation

(p.387) Chapter 15 Latent Variable Models for Analyzing DNA Methylation
Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

E. Andrés Houseman

Oxford University Press

Deoxyribonucleic acid (DNA) methylation is tightly linked with cellular differentiation. For instance, it has been observed that DNA methylation in tumor cells encodes phenotypic information about the tumor. Thus, understanding of tumor biology is fruitfully enhanced by the study of the multivariate structure of DNA methylation data. To the extent that such data possess discrete latent structure, it can be viewed as encoding different tumor subtypes (in cancer studies) or tissue types (more generally). However, in some cases there may be more evidence of continuous latent structure reflecting a continuous range of variation. This chapter discusses several specific latent variable models that have been used in the last decade to analyze DNA methylation data, including approaches for modeling DNA methylation data in low-dimensional settings such as in candidate gene studies and recursively partitioned mixture model approaches for modeling DNA methylation in high-dimensional settings.

Keywords:   DNA methylation, latent variable models, recursively partitioned mixture models

Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .