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ToolsStjernqvist, Susann, Ryden, Tobias and Greenman, Chris D. (2011) Model-integrated estimation of normal tissue contamination for cancer SNP allelic copy number data. Cancer Informatics, 10. pp. 159-173. ISSN 1176-9351
Full text not available from this repository. (Request a copy)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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Computational Biology |
| Depositing User: | Users 2731 not found. |
| Date Deposited: | 20 Feb 2012 14:11 |
| Last Modified: | 13 Jan 2024 01:20 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/37243 |
| DOI: | 10.4137/CIN.S6873 |
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