@article{ff496cefd9d14a0abfef847a3efde103,
title = "THetA: Inferring intra-tumor heterogeneity from high-throughput DNA sequencing data",
abstract = "Tumor samples are typically heterogeneous, containing admixture by normal, non-cancerous cells and one or more subpopulations of cancerous cells. Whole-genome sequencing of a tumor sample yields reads from this mixture, but does not directly reveal the cell of origin for each read. We introduce THetA (Tumor Heterogeneity Analysis), an algorithm that infers the most likely collection of genomes and their proportions in a sample, for the case where copy number aberrations distinguish subpopulations. THetA successfully estimates normal admixture and recovers clonal and subclonal copy number aberrations in real and simulated sequencing data. THetA is available at http://compbio.cs.brown.edu/software/.",
keywords = "Algorithms, Cancer genomics, DNA sequencing, Intra-tumor heterogeneity, Tumor evolution",
author = "Layla Oesper and Ahmad Mahmoody and Raphael, {Benjamin J.}",
note = "Funding Information: We thank Peter Campbell and Adam Butler for their assistance in obtaining the breast cancer data from EGA. We also thank Li Ding and Chris Miller for their assistance is selecting the AML genome from TCGA used in the simulations. The results published here are in whole or part based upon data generated by The Cancer Genome Atlas pilot project established by the National Cancer Institute and the National Human Genome Research Institute. Information about TCGA and the investigators and institutions that constitute the TCGA research network can be found at [62]. This work is supported by a National Science Foundation (NSF) graduate research fellowship DGE0228243 (LO), NSF career award CCF-1053753 (BJR) and grant RO1 HG5690 from the National Institutes of Health (BJR). BJR is also supported by a Career Award at the Scientific Interface from the Burroughs Wellcome Fund, an Alfred P Sloan Research Fellowship. Publisher Copyright: {\textcopyright} 2013 Oesper et al.",
year = "2013",
doi = "10.1186/gb-2013-14-7-r80",
language = "English (US)",
volume = "14",
journal = "Genome Biology",
issn = "1474-7596",
publisher = "BioMed Central",
number = "7",
}