highly sensitive and specific detection of rare variants in mixed viral populations from massively parallel sequence data高度敏感和具体检测混合的罕见变异病毒的数量由大规模并行序列数据.pdfVIP

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highly sensitive and specific detection of rare variants in mixed viral populations from massively parallel sequence data高度敏感和具体检测混合的罕见变异病毒的数量由大规模并行序列数据.pdf

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highly sensitive and specific detection of rare variants in mixed viral populations from massively parallel sequence data高度敏感和具体检测混合的罕见变异病毒的数量由大规模并行序列数据

Highly Sensitive and Specific Detection of Rare Variants in Mixed Viral Populations from Massively Parallel Sequence Data 1,2 1 1 1 1 Alexander R. Macalalad , Michael C. Zody , Patrick Charlebois , Niall J. Lennon , Ruchi M. Newman , 1 1 3 3 4 Christine M. Malboeuf , Elizabeth M. Ryan , Christian L. Boutwell , Karen A. Power , Doug E. Brackney , 4 1 4 3 1 Kendra N. Pesko , Joshua Z. Levin , Gregory D. Ebel , Todd M. Allen , Bruce W. Birren , Matthew R. Henn1* 1 Broad Institute of MIT Harvard, Cambridge, Massachusetts, United States of America, 2 Department of Biostatistics, Harvard University, Boston, Massachusetts, United States of America, 3 Ragon Institute of MGH, MIT and Harvard, Boston, Massachusetts, United States of America, 4 Department of Pathology, University of New Mexico School of Medicine, Albuquerque, New Mexico, United States of America Abstract Viruses diversify over time within hosts, often undercutting the effectiveness of host defenses and therapeutic interventions. To design successful vaccines and therapeutics, it is critical to better understand viral diversification, including comprehensively characterizing the genetic variants in viral intra-host populations and modeling changes from transmission through the course of infection. Massively parallel sequencing technologies can overcome the cost constraints of older sequencing methods and obtain the high sequence coverage needed to