%0 Journal Article %1 Griffith2015Optimizing %A Griffith, Malachi %A Miller, Christopher A. %A Griffith, Obi L. %A Krysiak, Kilannin %A Skidmore, Zachary L. %A Ramu, Avinash %A Walker, Jason R. %A Dang, Ha X. %A Trani, Lee %A Larson, David E. %A Demeter, Ryan T. %A Wendl, Michael C. %A McMichael, Joshua F. %A Austin, Rachel E. %A Magrini, Vincent %A McGrath, Sean D. %A Ly, Amy %A Kulkarni, Shashikant %A Cordes, Matthew G. %A Fronick, Catrina C. %A Fulton, Robert S. %A Maher, Christopher A. %A Ding, Li %A Klco, Jeffery M. %A Mardis, Elaine R. %A Ley, Timothy J. %A Wilson, Richard K. %D 2015 %I Elsevier %J Cell Systems %K cancer ibse next-generation-sequencing %N 3 %P 210--223 %R 10.1016/j.cels.2015.08.015 %T Optimizing Cancer Genome Sequencing and Analysis %U http://dx.doi.org/10.1016/j.cels.2015.08.015 %V 1 %X Current sequencing strategies are inadequate given the complexity of most tumors Current analysis strategies perform poorly, missing rare clinically relevant variants A comprehensive strategy allows for a more definitive model of tumor clonal architecture We present a comprehensively sequenced and validated case as a community resource Tumors are typically sequenced to depths of 75x–100x (exome) or 30x–50x (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 ∼312x) whole genome sequencing and exome capture (up to ∼433x) 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 ∼1,000x. Additional targeted sequencing provided over 10,000x coverage and ddPCR assays provided up to ∼250,000x 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: phs000159).

@article{Griffith2015Optimizing, abstract = { Current sequencing strategies are inadequate given the complexity of most tumors Current analysis strategies perform poorly, missing rare clinically relevant variants A comprehensive strategy allows for a more definitive model of tumor clonal architecture We present a comprehensively sequenced and validated case as a community resource Tumors are typically sequenced to depths of 75x–100x (exome) or 30x–50x (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 ∼312x) whole genome sequencing and exome capture (up to ∼433x) 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 ∼1,000x. Additional targeted sequencing provided over 10,000x coverage and {ddPCR} assays provided up to ∼250,000x 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}: phs000159). }, added-at = {2018-12-02T16:09:07.000+0100}, author = {Griffith, Malachi and Miller, Christopher A. and Griffith, Obi L. and Krysiak, Kilannin and Skidmore, Zachary L. and Ramu, Avinash and Walker, Jason R. and Dang, Ha X. and Trani, Lee and Larson, David E. and Demeter, Ryan T. and Wendl, Michael C. and McMichael, Joshua F. and Austin, Rachel E. and Magrini, Vincent and McGrath, Sean D. and Ly, Amy and Kulkarni, Shashikant and Cordes, Matthew G. and Fronick, Catrina C. and Fulton, Robert S. and Maher, Christopher A. and Ding, Li and Klco, Jeffery M. and Mardis, Elaine R. and Ley, Timothy J. and Wilson, Richard K.}, biburl = {https://www.bibsonomy.org/bibtex/2920dbee88c300feedcb9e3e450717688/karthikraman}, citeulike-article-id = {13798541}, citeulike-linkout-0 = {http://www.cell.com/cell-systems/abstract/S2405-4712(15)00113-1}, citeulike-linkout-1 = {http://dx.doi.org/10.1016/j.cels.2015.08.015}, day = 9, doi = {10.1016/j.cels.2015.08.015}, interhash = {1014b18fc34ba136f367916e43efe3b3}, intrahash = {920dbee88c300feedcb9e3e450717688}, issn = {24054712}, journal = {Cell Systems}, keywords = {cancer ibse next-generation-sequencing}, month = sep, number = 3, pages = {210--223}, posted-at = {2015-11-03 10:15:53}, priority = {2}, publisher = {Elsevier}, timestamp = {2018-12-02T16:09:07.000+0100}, title = {Optimizing Cancer Genome Sequencing and Analysis}, url = {http://dx.doi.org/10.1016/j.cels.2015.08.015}, volume = 1, year = 2015 }