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Statistical Analysis of Single Nucleotide Polymorphism Microarrays in Cancer Studies

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Handbook of Statistical Bioinformatics

Part of the book series: Springer Handbooks of Computational Statistics ((SHCS))

Abstract

In this chapter, we focus on statistical questions raised by the identification of copy number alterations in tumor samples using genotyping microarrays, also known as Single Nucleotide Polymorphism (SNP) arrays. We define the copy number states formally, and show how they are assessed by SNP arrays. We identify and discuss general and cancer-specific challenges for SNP array data preprocessing, and how they are addressed by existing methods. We review existing statistical methods for the detection of copy number changes along the genome. We describe the influence of two biological parameters – the proportion of normal cells in the sample, and the ploidy of the tumor – on observed data. Finally, we discuss existing approaches for the detection and calling of copy number aberrations in the particular context of cancer studies, and identify statistical challenges that remain to be addressed.

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Acknowledgements

We gratefully acknowledge the Lawrence Berkeley National Laboratory (LBNL) and The Cancer Genome Atlas (TCGA) for making data and results available. This work was supported by NCI grant U24 CA126551.

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Authors and Affiliations

  1. Department of Statistics, University of California, Berkeley, USA

    Pierre Neuvial, Henrik Bengtsson & Terence P. Speed

  2. Laboratoire Statistique et Génome, Université d’Évry Val d’Essonne, UMR CNRS 8071-USC INRA, Evry, France

    Pierre Neuvial

  3. Department of Epidemiology & Biostatistics, University of California, San Francisco, USA

    Henrik Bengtsson

  4. Bioinformatics Division, Walter & Eliza Hall Institute of Medical Research, Parkville, Australia

    Terence P. Speed

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  1. , Institute of Statistics, National Chiao Tung University, Ta Hsueh Road 1001, Hsinchu, 30050, Taiwan, Taiwan R.O.C.

    Henry Horng-Shing Lu

  2. , Department of Empirical Inference, MPI for Intelligent Systems, Spemannstraße 38, Tübingen, 72076, Germany

    Bernhard Schölkopf

  3. School of Medicine, Dept. Epidemiology & Public Health, Yale University, College Street 60, New Haven, 06520, Connecticut, USA

    Hongyu Zhao

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Neuvial, P., Bengtsson, H., Speed, T.P. (2011). Statistical Analysis of Single Nucleotide Polymorphism Microarrays in Cancer Studies. In: Lu, HS., Schölkopf, B., Zhao, H. (eds) Handbook of Statistical Bioinformatics. Springer Handbooks of Computational Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16345-6_11

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