Skip Navigation


Biostatistics Advance Access originally published online on December 22, 2007
Biostatistics 2008 9(3):484-500; doi:10.1093/biostatistics/kxm048
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Supplementary Material
Right arrow All Versions of this Article:
9/3/484    most recent
kxm048v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Van Wieringen, W. N.
Right arrow Articles by Ylstra, B.
PubMed
Right arrow PubMed Citation
Right arrow Articles by Van Wieringen, W. N.
Right arrow Articles by Ylstra, B.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2007. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.

Weighted clustering of called array CGH data

Wessel N. Van Wieringen*

Department of Mathematics, Vrije Universiteit, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands
wvanwie{at}few.vu.nl

Mark A. Van De Wiel

Department of Mathematics, Vrije Universiteit, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands, Department of Pathology, VU University Medical Center, PO Box 7075, 1007 MB Amsterdam, The Netherlands, and Department of Biostatistics, VU University Medical Center, PO Box 7075, 1007 MB Amsterdam, The Netherlands

Bauke Ylstra

Department of Pathology, VU University Medical Center, PO Box 7075, 1007 MB Amsterdam, The Netherlands

* To whom correspondence should be addressed.

Array comparative genomic hybridization (aCGH) is a laboratory technique to measure chromosomal copy number changes. A clear biological interpretation of the measurements is obtained by mapping these onto an ordinal scale with categories loss/normal/gain of a copy. The pattern of gains and losses harbors a level of tumor specificity. Here, we present WECCA (weighted clustering of called aCGH data), a method for weighted clustering of samples on the basis of the ordinal aCGH data. Two similarities to be used in the clustering and particularly suited for ordinal data are proposed, which are generalized to deal with weighted observations. In addition, a new form of linkage, especially suited for ordinal data, is introduced. In a simulation study, we show that the proposed cluster method is competitive to clustering using the continuous data. We illustrate WECCA using an application to a breast cancer data set, where WECCA finds a clustering that relates better with survival than the original one.

Keywords: Array CGH; Hierarchical clustering; Linkage; Ordinal data; Similarity; WECCA; Weighting

Received October 5, 2006; revised August 17, 2007; revised October 12, 2007; accepted for publication November 20, 2007.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.