Document Type
Journal Article
Publication Date
6-2012
Journal
Journal of Computational Biology
Volume
Volume 19, Issue 6
Inclusive Pages
679-693
Keywords
Chromosomes, Human, Pair 20--genetics; Chromosomes, Human, Pair 21--genetics; DNA, Neoplasm; Neoplasms--genetics; Polymorphism, Single Nucleotide
Abstract
The recent genome-wide allele-specific copy number variation data enable us to explore two types of genomic information including chromosomal genotype variations as well as DNA copy number variations. For a cancer study, it is common to collect data for paired normal and tumor samples. Then, two types of paired data can be obtained to study a disease subject. However, there is a lack of methods for a simultaneous analysis of these four sequences of data. In this study, we propose a statistical framework based on the change-point analysis approach. The validity and usefulness of our proposed statistical framework are demonstrated through the simulation studies and applications based on an experimental data set.
APA Citation
Lai, Y. (2012). Change-point analysis of paired allele-specific copy number variation data. Journal of Computational Biology, 19(6), 679-693.
Peer Reviewed
1
Open Access
1
Comments
This is a copy of an article published in the Journal of Computational Biology © 2012 copyright Mary Ann Liebert, Inc.; Journal of Computational Biology is available online at: http://online.liebertpub.com.