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  1. Home
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Browsing by Author "Tzen, Anthony"

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    SiFit: inferring tumor trees from single-cell sequencing data under finite-sites models
    (BioMed Central, 9/19/2017) Zafar, Hamim; Tzen, Anthony; Navin, Nicholas; Chen, Ken; Nakhleh, Luay
    Abstract Single-cell sequencing enables the inference of tumor phylogenies that provide insights on intra-tumor heterogeneity and evolutionary trajectories. Recently introduced methods perform this task under the infinite-sites assumption, violations of which, due to chromosomal deletions and loss of heterozygosity, necessitate the development of inference methods that utilize finite-sites models. We propose a statistical inference method for tumor phylogenies from noisy single-cell sequencing data under a finite-sites model. The performance of our method on synthetic and experimental data sets from two colorectal cancer patients to trace evolutionary lineages in primary and metastatic tumors suggests that employing a finite-sites model leads to improved inference of tumor phylogenies.
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