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Title: Analyzing cancer samples with SNP arrays
Authors: Van Loo, Peter ×
Nilsen, Gro
Nordgard, Silje H
Vollan, Hans Kristian Moen
Børresen-Dale, Anne-Lise
Kristensen, Vessela N
Lingjærde, Ole Christian #
Issue Date: 2012
Series Title: Methods in Molecular Biology vol:802 pages:57-72
Article number: 10.1007/978-1-61779-400-1_4
Abstract: Single nucleotide polymorphism (SNP) arrays are powerful tools to delineate genomic aberrations in cancer genomes. However, the analysis of these SNP array data of cancer samples is complicated by three phenomena: (a) aneuploidy: due to massive aberrations, the total DNA content of a cancer cell can differ significantly from its normal two copies; (b) nonaberrant cell admixture: samples from solid tumors do not exclusively contain aberrant tumor cells, but always contain some portion of nonaberrant cells; (c) intratumor heterogeneity: different cells in the tumor sample may have different aberrations. We describe here how these phenomena impact the SNP array profile, and how these can be accounted for in the analysis. In an extended practical example, we apply our recently developed and further improved ASCAT (allele-specific copy number analysis of tumors) suite of tools to analyze SNP array data using data from a series of breast carcinomas as an example. We first describe the structure of the data, how it can be plotted and interpreted, and how it can be segmented. The core ASCAT algorithm next determines the fraction of nonaberrant cells and the tumor ploidy (the average number of DNA copies), and calculates an ASCAT profile. We describe how these ASCAT profiles visualize both copy number aberrations as well as copy-number-neutral events. Finally, we touch upon regions showing intratumor heterogeneity, and how they can be detected in ASCAT profiles. All source code and data described here can be found at our ASCAT Web site ( http://www.ifi.uio.no/forskning/grupper/bioinf/Projects/ASCAT/).
URI: 
ISSN: 1064-3745
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Human Genome Laboratory
× corresponding author
# (joint) last author

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