CGHregions: Dimension Reduction for Array CGH Data with Minimal Information Loss

• Main Authors: Mark A. van de Wiel, Wessel N. van Wieringen
• Format: Article
• Language: English
• Published: SAGE Publishing 2007-01-01
• Series: Cancer Informatics
• Subjects: Array CGH; Dimension reduction; Tumor profiles; Statistical testing; FDR
• Online Access: http://la-press.com/article.php?article_id=47

An algorithm to reduce multi-sample array CGH data from thousands of clones to tens or hundreds of clone regions is introduced. This reduction of the data is performed such that little information is lost, which is possible due to the high dependencies between neighboring clones. The algorithm is explained using a small example. The potential beneficial effects of the algorithm for downstream analysis are illustrated by re-analysis of previously published colorectal cancer data. Using multiple testing corrections suitable for these data, we provide statistical evidence for genomic differences on several clone regions between MSI+ and CIN+ tumors. The algorithm, named CGHregions, is available as an easy-to-use script in R.