Visualization of Genomic Changes by Segmented Smoothing Using an L (0) Penalty

Copy number variations (CNV) and allelic imbalance in tumor tissue can show strong segmentation. Their graphical presentation can be enhanced by appropriate smoothing. Existing signal and scatterplot smoothers do not respect segmentation well. We present novel algorithms that use a penalty on the [I...

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Detalles Bibliográficos
Autores principales: Rippe, Ralph C. A., Meulman, Jacqueline J., Eilers, Paul H. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3367998/
https://www.ncbi.nlm.nih.gov/pubmed/22679492
http://dx.doi.org/10.1371/journal.pone.0038230
Descripción
Sumario:Copy number variations (CNV) and allelic imbalance in tumor tissue can show strong segmentation. Their graphical presentation can be enhanced by appropriate smoothing. Existing signal and scatterplot smoothers do not respect segmentation well. We present novel algorithms that use a penalty on the [Image: see text] norm of differences of neighboring values. Visualization is our main goal, but we compare classification performance to that of VEGA.

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