Skip Navigation


Bioinformatics Advance Access originally published online on November 30, 2004
Bioinformatics 2005 21(7):1146-1153; doi:10.1093/bioinformatics/bti148
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow All Versions of this Article:
21/7/1146    most recent
bti148v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
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 ISI Web of Science
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 arrow Search for citing articles in:
ISI Web of Science (30)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Eilers, P. H. C.
Right arrow Articles by de Menezes, R. X.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Eilers, P. H. C.
Right arrow Articles by de Menezes, R. X.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2004. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Quantile smoothing of array CGH data

Paul H. C. Eilers * and Renée X. de Menezes

Department of Medical Statistics, Leiden University Medical Centre PO Box 9604, 2300 RC, Leiden, The Netherlands

*To whom correspondence should be addressed.

Motivation: Plots of array Comparative Genomic Hybridization (CGH) data often show special patterns: stretches of constant level (copy number) with sharp jumps between them. There can also be much noise. Classic smoothing algorithms do not work well, because they introduce too much rounding. To remedy this, we introduce a fast and effective smoothing algorithm based on penalized quantile regression. It can compute arbitrary quantile curves, but we concentrate on the median to show the trend and the lower and upper quartile curves showing the spread of the data. Two-fold cross-validation is used for optimizing the weight of the penalties.

Results: Simulated data and a published dataset are used to show the capabilities of the method to detect the segments of changed copy numbers in array CGH data.

Availability: Software for R and Matlab is available.

Contact: p.eilers{at}lumc.nl


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


This article has been cited by other articles:


Home page
 GeneticsHome page
B. Daines, H. Wang, Y. Li, Y. Han, R. Gibbs, and R. Chen
High-Throughput Multiplex Sequencing to Discover Copy Number Variants in Drosophila
Genetics, August 1, 2009; 182(4): 935 - 941.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
E. Budinska, E. Gelnarova, and M. G. Schimek
MSMAD: a computationally efficient method for the analysis of noisy array CGH data
Bioinformatics, March 15, 2009; 25(6): 703 - 713.
[Abstract] [Full Text] [PDF]

Home page
 Genome ResHome page
L.-y. Wang, A. Abyzov, J. O. Korbel, M. Snyder, and M. Gerstein
MSB: A mean-shift-based approach for the analysis of structural variation in the genome
Genome Res., January 1, 2009; 19(1): 106 - 117.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
R. Andersson, C. E. G. Bruder, A. Piotrowski, U. Menzel, H. Nord, J. Sandgren, T. R. Hvidsten, T. Diaz de Stahl, J. P. Dumanski, and J. Komorowski
A segmental maximum a posteriori approach to genome-wide copy number profiling
Bioinformatics, March 15, 2008; 24(6): 751 - 758.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
S. Stjernqvist, T. Ryden, M. Skold, and J. Staaf
Continuous-index hidden Markov modelling of array CGH copy number data
Bioinformatics, April 15, 2007; 23(8): 1006 - 1014.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
J. Hu, J.-B. Gao, Y. Cao, E. Bottinger, and W. Zhang
Exploiting noise in array CGH data to improve detection of DNA copy number change
Nucleic Acids Res., March 12, 2007; 35(5): e35 - e35.
[Abstract] [Full Text] [PDF]

Home page
 Genome ResHome page
J. Oosting, E. H. Lips, R. van Eijk, P. H.C. Eilers, K. Szuhai, C. Wijmenga, H. Morreau, and T. van Wezel
High-resolution copy number analysis of paraffin-embedded archival tissue using SNP BeadArrays
Genome Res., March 1, 2007; 17(3): 368 - 376.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
P. L. Rosa, E. Viara, P. Hupe, G. Pierron, S. Liva, P. Neuvial, I. Brito, S. Lair, N. Servant, N. Robine, et al.
VAMP: Visualization and analysis of array-CGH, transcriptome and other molecular profiles
Bioinformatics, September 1, 2006; 22(17): 2066 - 2073.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Res.Home page
J. Cardoso, L. Molenaar, R. X. de Menezes, M. van Leerdam, C. Rosenberg, G. Moslein, J. Sampson, H. Morreau, J. M. Boer, and R. Fodde
Chromosomal Instability in MYH- and APC-Mutant Adenomatous Polyps.
Cancer Res., March 1, 2006; 66(5): 2514 - 2519.
[Abstract] [Full Text] [PDF]

Home page
 Nucleic Acids ResHome page
J. Knijnenburg, M. van der Burg, P. Nilsson, H. K. P. van Amstel, H. Tanke, and K. Szuhai
Rapid detection of genomic imbalances using micro-arrays consisting of pooled BACs covering all human chromosome arms
Nucleic Acids Res., October 12, 2005; 33(18): e159 - e159.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
W. R. Lai, M. D. Johnson, R. Kucherlapati, and P. J. Park
Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data
Bioinformatics, October 1, 2005; 21(19): 3763 - 3770.
[Abstract] [Full Text] [PDF]

Home page
 BioinformaticsHome page
A. A. Margolin, J. Greshock, T. L. Naylor, Y. Mosse, J. M. Maris, G. Bignell, A. I. Saeed, J. Quackenbush, and B. L. Weber
CGHAnalyzer: a stand-alone software package for cancer genome analysis using array-based DNA copy number data
Bioinformatics, August 1, 2005; 21(15): 3308 - 3311.
[Abstract] [Full Text] [PDF]


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.