Methods for derivation of LOH and allelic copy numbers using SNP arrays

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Methods for derivation of LOH and allelic copy numbers using SNP arrays. / Wiuf, Carsten; Lamy, Philippe; Andersen, Claus L.

Statistics and Informatics in Molecular Cancer Research. Vol. 9780199532872 Oxford University Press, 2009.

Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

Harvard

Wiuf, C, Lamy, P & Andersen, CL 2009, Methods for derivation of LOH and allelic copy numbers using SNP arrays. in Statistics and Informatics in Molecular Cancer Research. vol. 9780199532872, Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199532872.003.0003

APA

Wiuf, C., Lamy, P., & Andersen, C. L. (2009). Methods for derivation of LOH and allelic copy numbers using SNP arrays. In Statistics and Informatics in Molecular Cancer Research (Vol. 9780199532872). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199532872.003.0003

Vancouver

Wiuf C, Lamy P, Andersen CL. Methods for derivation of LOH and allelic copy numbers using SNP arrays. In Statistics and Informatics in Molecular Cancer Research. Vol. 9780199532872. Oxford University Press. 2009 https://doi.org/10.1093/acprof:oso/9780199532872.003.0003

Author

Wiuf, Carsten ; Lamy, Philippe ; Andersen, Claus L. / Methods for derivation of LOH and allelic copy numbers using SNP arrays. Statistics and Informatics in Molecular Cancer Research. Vol. 9780199532872 Oxford University Press, 2009.

Bibtex

@inbook{4957dd0954a9426a89db4d3cc38a5cde,

title = "Methods for derivation of LOH and allelic copy numbers using SNP arrays",

abstract = "This chapter discusses statistical methods to derive loss-of-heterozygosity (LOH) and allele specific copy numbers in cancer cells. SNP arrays enable simultaneous information about thousands of DNA markers and their allele specific copy numbers, but to extract the information advanced statistical tools are required. The chapter shows how Hidden Markov Models (HMM) can be applied to infer LOH from genotype data and how the allele intensities are informative about allelic copy number. The methods are illustrated by examples.",

keywords = "Allelic copy number, DNA marker, Genotype, Hidden markov model, Loss-of-heterozygosity",

author = "Carsten Wiuf and Philippe Lamy and Andersen, {Claus L.}",

year = "2009",

month = sep,

day = "1",

doi = "10.1093/acprof:oso/9780199532872.003.0003",

language = "English",

isbn = "9780199532872",

volume = "9780199532872",

booktitle = "Statistics and Informatics in Molecular Cancer Research",

publisher = "Oxford University Press",

address = "United Kingdom",

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RIS

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AU - Wiuf, Carsten

AU - Lamy, Philippe

AU - Andersen, Claus L.

PY - 2009/9/1

Y1 - 2009/9/1

N2 - This chapter discusses statistical methods to derive loss-of-heterozygosity (LOH) and allele specific copy numbers in cancer cells. SNP arrays enable simultaneous information about thousands of DNA markers and their allele specific copy numbers, but to extract the information advanced statistical tools are required. The chapter shows how Hidden Markov Models (HMM) can be applied to infer LOH from genotype data and how the allele intensities are informative about allelic copy number. The methods are illustrated by examples.

AB - This chapter discusses statistical methods to derive loss-of-heterozygosity (LOH) and allele specific copy numbers in cancer cells. SNP arrays enable simultaneous information about thousands of DNA markers and their allele specific copy numbers, but to extract the information advanced statistical tools are required. The chapter shows how Hidden Markov Models (HMM) can be applied to infer LOH from genotype data and how the allele intensities are informative about allelic copy number. The methods are illustrated by examples.

KW - Allelic copy number

KW - DNA marker

KW - Genotype

KW - Hidden markov model

KW - Loss-of-heterozygosity

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SN - 9780199532872

VL - 9780199532872

BT - Statistics and Informatics in Molecular Cancer Research

PB - Oxford University Press

ER -

ID: 203899912