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Model-integrated estimation of normal tissue contamination for cancer SNP allelic copy number data.

Stjernqvist, Susann LU ; Rydén, Tobias LU and Greenman, Chris D (2011) In Cancer Informatics p.159-173
Abstract
SNP allelic copy number data provides intensity measurements for the two different alleles separately. We present a method that estimates the number of copies of each allele at each SNP position, using a continuous-index hidden Markov model. The method is especially suited for cancer data, since it includes the fraction of normal tissue contamination, often present when studying data from cancer tumors, into the model. The continuous-index structure takes into account the distances between the SNPs, and is thereby appropriate also when SNPs are unequally spaced. In a simulation study we show that the method performs favorably compared to previous methods even with as much as 70% normal contamination. We also provide results from... (More)
SNP allelic copy number data provides intensity measurements for the two different alleles separately. We present a method that estimates the number of copies of each allele at each SNP position, using a continuous-index hidden Markov model. The method is especially suited for cancer data, since it includes the fraction of normal tissue contamination, often present when studying data from cancer tumors, into the model. The continuous-index structure takes into account the distances between the SNPs, and is thereby appropriate also when SNPs are unequally spaced. In a simulation study we show that the method performs favorably compared to previous methods even with as much as 70% normal contamination. We also provide results from applications to clinical data produced using the Affymetrix genome-wide SNP 6.0 platform. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Cancer Informatics
issue
10
pages
159 - 173
publisher
Libertas Academica
external identifiers
  • scopus:80053618718
ISSN
1176-9351
DOI
10.4137/CIN.S6873
language
English
LU publication?
yes
id
30c22415-1f81-4437-9b39-411fb243ffa9 (old id 2007864)
date added to LUP
2011-08-23 16:40:12
date last changed
2017-01-01 06:34:48
@article{30c22415-1f81-4437-9b39-411fb243ffa9,
  abstract     = {SNP allelic copy number data provides intensity measurements for the two different alleles separately. We present a method that estimates the number of copies of each allele at each SNP position, using a continuous-index hidden Markov model. The method is especially suited for cancer data, since it includes the fraction of normal tissue contamination, often present when studying data from cancer tumors, into the model. The continuous-index structure takes into account the distances between the SNPs, and is thereby appropriate also when SNPs are unequally spaced. In a simulation study we show that the method performs favorably compared to previous methods even with as much as 70% normal contamination. We also provide results from applications to clinical data produced using the Affymetrix genome-wide SNP 6.0 platform.},
  author       = {Stjernqvist, Susann and Rydén, Tobias and Greenman, Chris D},
  issn         = {1176-9351},
  language     = {eng},
  number       = {10},
  pages        = {159--173},
  publisher    = {Libertas Academica},
  series       = {Cancer Informatics},
  title        = {Model-integrated estimation of normal tissue contamination for cancer SNP allelic copy number data.},
  url          = {http://dx.doi.org/10.4137/CIN.S6873},
  year         = {2011},
}