Journal Article

Smoothing waves in array CGH tumor profiles

Mark A. van de Wiel, Rebecca Brosens, Paul H. C. Eilers, Candy Kumps, Gerrit A. Meijer, Björn Menten, Erik Sistermans, Frank Speleman, Marieke E. Timmerman and Bauke Ylstra

in Bioinformatics

Volume 25, issue 9, pages 1099-1104
Published in print May 2009 | ISSN: 1367-4803
Published online March 2009 | e-ISSN: 1460-2059 | DOI:
Smoothing waves in array CGH tumor profiles

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  • Bioinformatics and Computational Biology


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Motivation: Many high-resolution array comparative genomic hybridization tumor profiles contain a wave bias, which makes accurate detection of breakpoints in such profiles more difficult.

Results: An efficient and highly effective algorithm that largely removes the wave bias from tumor profiles by regressing the tumor profile data on data of profiles from the clinical genetics practice. Results are illustrated on two independent datasets. The algorithm is shown to be robust against the presence of true copy number aberrations. Moreover, the smoothed profiles are able to recapitulate the aberration location and signal for simulated tumor profiles.

Availability: Easy-to-use R scripts, user instructions and data are available from


Supplementary information: Supplementary information are available at Bioinformatics online.

Journal Article.  3854 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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