TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays

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Author
Bengtsson, H; Neuvial, P; Speed, TPDate
2010-05-12Source Title
BMC BioinformaticsPublisher
BMCUniversity of Melbourne Author/s
Speed, TerenceAffiliation
School of Mathematics and StatisticsMetadata
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Journal ArticleCitations
Bengtsson, H., Neuvial, P. & Speed, T. P. (2010). TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays. BMC BIOINFORMATICS, 11 (1), https://doi.org/10.1186/1471-2105-11-245.Access Status
Open AccessAbstract
BACKGROUND: High-throughput genotyping microarrays assess both total DNA copy number and allelic composition, which makes them a tool of choice for copy number studies in cancer, including total copy number and loss of heterozygosity (LOH) analyses. Even after state of the art preprocessing methods, allelic signal estimates from genotyping arrays still suffer from systematic effects that make them difficult to use effectively for such downstream analyses. RESULTS: We propose a method, TumorBoost, for normalizing allelic estimates of one tumor sample based on estimates from a single matched normal. The method applies to any paired tumor-normal estimates from any microarray-based technology, combined with any preprocessing method. We demonstrate that it increases the signal-to-noise ratio of allelic signals, making it significantly easier to detect allelic imbalances. CONCLUSIONS: TumorBoost increases the power to detect somatic copy-number events (including copy-neutral LOH) in the tumor from allelic signals of Affymetrix or Illumina origin. We also conclude that high-precision allelic estimates can be obtained from a single pair of tumor-normal hybridizations, if TumorBoost is combined with single-array preprocessing methods such as (allele-specific) CRMA v2 for Affymetrix or BeadStudio's (proprietary) XY-normalization method for Illumina. A bounded-memory implementation is available in the open-source and cross-platform R package aroma.cn, which is part of the Aroma Project (http://www.aroma-project.org/).
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