@article{28821f2658d34b01930e6911c101f738,
title = "A statistical approach for detecting genomic aberrations in heterogeneous tumor samples from single nucleotide polymorphism genotyping data",
abstract = "We describe a statistical method for the characterization of genomic aberrations in single nucleotide polymorphism microarray data acquired from cancer genomes. Our approach allows us to model the joint effect of polyploidy, normal DNA contamination and intra-tumour heterogeneity within a single unified Bayesian framework. We demonstrate the efficacy of our method on numerous datasets including laboratory generated mixtures of normal-cancer cell lines and real primary tumours.",
author = "Christopher Yau and Dmitri Mouradov and Jorissen, \{Robert N.\} and Stefano Colella and Ghazala Mirza and Graham Steers and Adrian Harris and Jiannis Ragoussis and Oliver Sieber and Holmes, \{Christopher C.\}",
note = "Funding Information: The authors would like to thank Jean-Baptiste Cazier for general discussions and careful reading of this manuscript, Rachel Natrajan and Jorge Reis-Filho for discussion and advice on earlier versions of the work and Dan Peiffer (Illumina) for providing the cell line data for HL-60 and HT-29. CY is funded by a UK Medical Research Council Specialist Training Fellowship in Biomedical Informatics (Reference No. G0701810) and previously by a UK Engineering and Physical Sciences Research Council Life Sciences Interface Doctoral Training Studentship. JR, GM and SC were supported by a Wellcome Trust Grant 075491/Z/04/Z. DM, RJ and OS were supported by the Hilton Ludwig Cancer Metastasis Initiative. OS is supported by National Health and Medical Research Council Project Grant 489418. We also thank the reviewers for useful comments.",
year = "2010",
month = sep,
day = "21",
doi = "10.1186/gb-2010-11-9-r92",
language = "English",
volume = "11",
journal = "Genome biology",
issn = "1465-6906",
publisher = "BioMed Central",
number = "9",
}