Model-integrated estimation of normal tissue contamination for cancer SNP allelic copy number data.
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2007864
- author
- Stjernqvist, Susann LU ; Rydén, Tobias LU and Greenman, Chris D
- organization
- publishing date
- 2011
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Cancer Informatics
- issue
- 10
- pages
- 159 - 173
- publisher
- Libertas Academica
- external identifiers
-
- scopus:80053618718
- pmid:21695067
- ISSN
- 1176-9351
- DOI
- 10.4137/CIN.S6873
- language
- English
- LU publication?
- yes
- additional info
- - Affiliation: Centre for Mathematical Sciences, Lund University, Box 118, 221 00 Lund, Sweden, Department of Mathematics, Royal Institute of Technology, 100 44 Stockholm, Sweden.
- id
- 30c22415-1f81-4437-9b39-411fb243ffa9 (old id 2007864)
- date added to LUP
- 2016-04-01 15:03:42
- date last changed
- 2022-01-28 03:54:10
@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}}, doi = {{10.4137/CIN.S6873}}, year = {{2011}}, }