Journal
PLOS ONE
Volume 7, Issue 9, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0045835
Keywords
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Categories
Funding
- National Health and Medical Research Council of Australia (NHMRC) [631701, 535903, 427601]
- Australian Government: Department of Innovation, Industry, Science and Research
- Australian Cancer Research Foundation
- Queensland Government (National and International Research Alliances Program)
- University of Queensland
- Cancer Council New South Wales (NSW) [SRP06-01]
- Cancer Institute NSW [06/ECF/1-24, 09/CDF/2-40, 07/CDF/1-03, 10/CRF/1-01, 08/RSA/1-15, 07/CDF/1-28, 10/CDF/2-26, 10/FRL/2-03, 06/RSA/1-05, 09/RIG/1-02, 10/TPG/1-04, 11/REG/1-10, 11/CDF/3-26]
- Garvan Institute of Medical Research
- Avner Nahmani Pancreatic Cancer Research Foundation
- R.T. Hall Trust
- Gastroenterological Society of Australia
- American Association for Cancer Research Landon Foundation INNOVATOR Award
- Royal Australasian College of Surgeons
- Royal Australasian College of Physicians
- Royal College of Pathologists of Australasia
- Petre Foundation
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Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 (p-value = 0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 (p-value < 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 (p-value = 0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.
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