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10.1016/j.cels.2015.08.015

http://scihub22266oqcxt.onion/10.1016/j.cels.2015.08.015
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C4669575!4669575!26645048
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suck abstract from ncbi

pmid26645048      Cell+Syst 2015 ; 1 (3): 210-23
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  • Optimizing cancer genome sequencing and analysis #MMPMID26645048
  • Griffith M; Miller CA; Griffith OL; Krysiak K; Skidmore ZL; Ramu A; Walker JR; Dang HX; Trani L; Larson DE; Demeter RT; Wendl MC; McMichael JF; Austin RE; Magrini V; McGrath SD; Ly A; Kulkarni S; Cordes MG; Fronick CC; Fulton RS; Maher CA; Ding L; Klco JM; Mardis ER; Ley TJ; Wilson RK
  • Cell Syst 2015[Sep]; 1 (3): 210-23 PMID26645048show ga
  • Tumors are typically sequenced to depths of 75?100× (exome) or 30?50× (whole genome). We demonstrate that current sequencing paradigms are inadequate for tumors that are impure, aneuploid or clonally heterogeneous. To reassess optimal sequencing strategies, we performed ultra-deep (up to ~312×) whole genome sequencing (WGS) and exome capture (up to ~433×) of a primary acute myeloid leukemia, its subsequent relapse, and a matched normal skin sample. We tested multiple alignment and variant calling algorithms and validated ~200,000 putative SNVs by sequencing them to depths of ~1,000×. Additional targeted sequencing provided over 10,000× coverage and ddPCR assays provided up to ~250,000× sampling of selected sites. We evaluated the effects of different library generation approaches, depth of sequencing, and analysis strategies on the ability to effectively characterize a complex tumor. This dataset, representing the most comprehensively sequenced tumor described to date, will serve as an invaluable community resource (dbGaP accession id phs000159).
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