@article{discovery10205418,
            note = {Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

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       publisher = {BMC},
          volume = {15},
            year = {2014},
           title = {Deciphering clonality in aneuploid breast tumors using SNP array and sequencing data},
         journal = {Genome Biology},
          number = {9},
        keywords = {Science \& Technology, Life Sciences \& Biomedicine, Biotechnology \& Applied Microbiology, Genetics \& Heredity, COPY NUMBER ANALYSIS, EVOLUTION, HETEROGENEITY, MUTATIONS, ALIGNMENT, CANCER, TOOL},
          author = {Loennstedt, Ingrid M and Caramia, Franco and Li, Jason and Fumagalli, Debora and Salgado, Roberto and Rowan, Andrew and Salm, Max and Kanu, Nnennaya and Savas, Peter and Horswell, Stuart and Gade, Stephan and Loibl, Sibylle and Neven, Patrick and Sotiriou, Christos and Swanton, Charles and Loi, Sherene and Speed, Terence P},
        abstract = {Intra-tumor heterogeneity concerns the existence of genetically different subclones within the same tumor. Single sample quantification of heterogeneity relies on precise determination of chromosomal copy numbers throughout the genome, and an assessment of whether identified mutation variant allele fractions match clonal or subclonal copy numbers. We discuss these issues using data from SNP arrays, whole exome sequencing and pathologist purity estimates on several breast cancers characterized by ERBB2 amplification. We show that chromosomal copy numbers can only be estimated from SNP array signals or sequencing depths for subclonal tumor samples with simple subclonal architectures under certain assumptions.},
             url = {https://doi.org/10.1186/preaccept-9755896761283690},
            issn = {1474-760X}
}