qpure: A Tool to Estimate Tumor Cellularity from Genome-Wide Single-Nucleotide Polymorphism Profiles

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; howe...

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Bibliographic Details
Published in:PloS one Vol. 7; no. 9; p. e45835
Main Authors: Song, Sarah, Nones, Katia, Miller, David, Harliwong, Ivon, Kassahn, Karin S., Pinese, Mark, Pajic, Marina, Gill, Anthony J., Johns, Amber L., Anderson, Matthew, Holmes, Oliver, Leonard, Conrad, Taylor, Darrin, Wood, Scott, Xu, Qinying, Newell, Felicity, Cowley, Mark J., Wu, Jianmin, Wilson, Peter, Fink, Lynn, Biankin, Andrew V., Waddell, Nic, Grimmond, Sean M., Pearson, John V.
Format: Journal Article
Language:English
Published: United States Public Library of Science 25.09.2012
Public Library of Science (PLoS)
Subjects:
Algorithms
Biology
Cancer
Cell Line, Tumor
Computational Biology - methods
Copy number
Correlation
Deoxyribonucleic acid
Discriminant analysis
DNA
DNA methylation
Estimates
Exons
Experiments
Gene expression
Gene Expression Regulation
Gene Frequency
Genetic aspects
Genetic testing
Genome-Wide Association Study
Genomes
Genomics
Heterogeneity
Heterozygosity
Humans
K-Ras protein
Lesions
Loss of Heterozygosity
Mathematical models
Mathematics
Medical research
Medicine
Models, Genetic
Models, Statistical
Mutation
Pancreatic cancer
Pancreatic Neoplasms - genetics
Pancreatic Neoplasms - metabolism
Parameter estimation
Pathology
Physiological aspects
Polymorphism
Polymorphism, Single Nucleotide
Regression Analysis
Reviews
Sensitivity analysis
Sequence Analysis, DNA
Single nucleotide polymorphisms
Single-nucleotide polymorphism
Software
Statistical analysis
Statistical methods
Statistical models
Tumors
Australia
Queensland Australia
St Lucia
New South Wales Australia
ISSN:1932-6203, 1932-6203
Online Access:Get full text
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Summary: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 ([Formula: see text]-value=0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 ([Formula: see text]-value [Formula: see text] 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 ([Formula: see text]-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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Competing Interests: The authors have declared that no competing interests exist.
Conceived and designed the experiments: SS NW JVP KSK. Performed the experiments: KN DM IH AJG M. Pinese M. Pajic. Analyzed the data: SS NW JVP. Contributed reagents/materials/analysis tools: ALJ AVB MA OH CL DT SW QX FN MJC JW LF PW. Wrote the paper: SS KN KSK LF NW SMG JVP.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0045835