A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods.
A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods.
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DOI：
10.1093/bioinformatics/btp074
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发表时间：
2009-04-01
期刊：
影响因子：
--
通讯作者：
Speed TP
中科院分区：
文献类型：
--
作者：
Bengtsson H;Ray A;Spellman P;Speed TP
动机：全基因组拷贝数（CN）研究的迅速扩大带来了对CN估计的精度和分辨率的提高的需求。最近的研究从一个以上的平台获得了同一组样本的氯化萘估计值，因此很自然地需要将不同的估计值进行联合收割机合并，以满足这一需求。不同平台的估算值显示氯化萘真实变化的衰减程度不同。在不同实验室运行的同一平台上，或在同一实验室采用不同分析方法运行的同一平台上，也可观察到氯化萘存在类似差异。这就是为什么不能直接将不同来源（平台、实验室和分析方法）的氯化萘估计值联合收割机合并起来的原因。结果：我们提出了一个单样本多源归一化，使全分辨率CN估计跨源相同的规模。标准化的氯化萘使得对于任何潜在的氯化萘水平，其平均水平是相同的，而不管来源如何，这使得它们更适合于跨来源组合，例如，现有的分割方法可用于识别异常区域。我们使用“癌症基因组图谱”（TCGA）项目中基于微阵列的CN估计来说明和验证该方法。我们表明，归一化和合并的数据更好地分离两个CN状态在给定的分辨率。我们的结论是，有可能将多个来源的氯化萘联合收割机组合起来，从而有效提高分辨率，而且当多个平台组合起来时，它们还可以通过在不同区域相互补充来提高基因组覆盖率。可用性：aroma.cn中提供了一个有界内存实现。联系方式：hb@stat.berkeley.edu
Motivation: The rapid expansion of whole-genome copy number (CN) studies brings a demand for increased precision and resolution of CN estimates. Recent studies have obtained CN estimates from more than one platform for the same set of samples, and it is natural to want to combine the different estimates in order to meet this demand. Estimates from different platforms show different degrees of attenuation of the true CN changes. Similar differences can be observed in CNs from the same platform run in different labs, or in the same lab, with different analytical methods. This is the reason why it is not straightforward to combine CN estimates from different sources (platforms, labs and analysis methods). Results: We propose a single-sample multi source normalization that brings full-resolution CN estimates to the same scale across sources. The normalized CNs are such that for any underlying CN level, their mean level is the same regardless of the source, which make them better suited for being combined across sources, e.g. existing segmentation methods may be used to identify aberrant regions. We use microarray-based CN estimates from ‘The Cancer Genome Atlas’ (TCGA) project to illustrate and validate the method. We show that the normalized and combined data better separate two CN states at a given resolution. We conclude that it is possible to combine CNs from multiple sources such that the resolution becomes effectively larger, and when multiple platforms are combined, they also enhance the genome coverage by complementing each other in different regions. Availability: A bounded-memory implementation is available in aroma.cn. Contact: hb@stat.berkeley.edu
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BAC到未来！或寡核苷酸：微阵列比较基因组杂交（阵列CGH）的视角。
影响因子：
14.9
作者：
Ylstra, B;van den IJssel, P;Carvalho, B;Brakenhoff, RH;Meijer, GA
通讯作者：
Meijer, GA
影响因子：
5.8
作者：
Marioni, JC;Thorne, NP;Tavaré, S
通讯作者：
Tavaré, S
影响因子：
64.8
作者：
Chin, L.;Meyerson, M.;Aldape, K.;Bigner, D.;Mikkelsen, T.;VandenBerg, S.;Kahn, A.;Penny, R.;Ferguson, M. L.;Gerhard, D. S.;Getz, G.;Brennan, C.;Taylor, B. S.;Winckler, W.;Park, P.;Ladanyi, M.;Hoadley, K. A.;Verhaak, R. G. W.;Hayes, D. N.;Spellman, Paul T.;Absher, D.;Weir, B. A.;Ding, L.;Wheeler, D.;Lawrence, M. S.;Cibulskis, K.;Mardis, E.;Zhang, Jinghui;Wilson, R. K.;Donehower, L.;Wheeler, D. A.;Purdom, E.;Wallis, J.;Laird, P. W.;Herman, J. G.;Schuebel, K. E.;Weisenberger, D. J.;Baylin, S. B.;Schultz, N.;Yao, Jun;Wiedemeyer, R.;Weinstein, J.;Sander, C.;Gibbs, R. A.;Gray, J.;Kucherlapati, R.;Lander, E. S.;Myers, R. M.;Perou, C. M.;McLendon, Roger;Friedman, Allan;Van Meir, Erwin G;Brat, Daniel J;Mastrogianakis, Gena Marie;Olson, Jeffrey J;Lehman, Norman;Yung, W. K. Alfred;Bogler, Oliver;Berger, Mitchel;Prados, Michael;Muzny, Donna;Morgan, Margaret;Scherer, Steve;Sabo, Aniko;Nazareth, Lynn;Lewis, Lora;Hall, Otis;Zhu, Yiming;Ren, Yanru;Alvi, Omar;Yao, Jiqiang;Hawes, Alicia;Jhangiani, Shalini;Fowler, Gerald;San Lucas, Anthony;Kovar, Christie;Cree, Andrew;Dinh, Huyen;Santibanez, Jireh;Joshi, Vandita;Gonzalez-Garay, Manuel L.;Miller, Christopher A.;Milosavljevic, Aleksandar;Sougnez, Carrie;Fennell, Tim;Mahan, Scott;Wilkinson, Jane;Ziaugra, Liuda;Onofrio, Robert;Bloom, Toby;Nicol, Rob;Ardlie, Kristin;Baldwin, Jennifer;Gabriel, Stacey;Fulton, Robert S.;McLellan, Michael D.;Larson, David E.;Shi, Xiaoqi;Abbott, Rachel;Fulton, Lucinda;Chen, Ken;Koboldt, Daniel C.;Wendl, Michael C.;Meyer, Rick;Tang, Yuzhu;Lin, Ling;Osborne, John R.;Dunford-Shore, Brian H.;Miner, Tracie L.;Delehaunty, Kim;Markovic, Chris;Swift, Gary;Courtney, William;Pohl, Craig;Abbott, Scott;Hawkins, Amy;Leong, Shin;Haipek, Carrie;Schmidt, Heather;Wiechert, Maddy;Vickery, Tammi;Scott, Sacha;Dooling, David J.;Chinwalla, Asif;Weinstock, George M.;O'Kelly, Michael;Robinson, Jim;Alexe, Gabriele;Beroukhim, Rameen;Carter, Scott;Chiang, Derek;Gould, Josh;Gupta, Supriya;Korn, Josh;Mermel, Craig;Mesirov, Jill;Monti, Stefano;Nguyen, Huy;Parkin, Melissa;Reich, Michael;Stransky, Nicolas;Garraway, Levi;Golub, Todd;Protopopov, Alexei;Perna, Ilana;Aronson, Sandy;Sathiamoorthy, Narayan;Ren, Georgia;Kim, Hyunsoo;Kong, Sek Won;Xiao, Yonghong;Kohane, Isaac S.;Seidman, Jon;Cope, Leslie;Pan, Fei;Van Den Berg, David;Van Neste, Leander;Yi, Joo Mi;Li, Jun Z.;Southwick, Audrey;Brady, Shannon;Aggarwal, Amita;Chung, Tisha;Sherlock, Gavin;Brooks, James D.;Jakkula, Lakshmi R.;Lapuk, Anna V.;Marr, Henry;Dorton, Shannon;Choi, Yoon Gi;Han, Ju;Ray, Amrita;Wang, Victoria;Durinck, Steffen;Robinson, Mark;Wang, Nicholas J.;Vranizan, Karen;Peng, Vivian;Van Name, Eric;Fontenay, Gerald V.;Ngai, John;Conboy, John G.;Parvin, Bahram;Feiler, Heidi S.;Speed, Terence P.;Socci, Nicholas D.;Olshen, Adam;Lash, Alex;Reva, Boris;Antipin, Yevgeniy;Stukalov, Alexey;Gross, Benjamin;Cerami, Ethan;Wang, Wei Qing;Qin, Li-Xuan;Seshan, Venkatraman E.;Villafania, Liliana;Cavatore, Magali;Borsu, Laetitia;Viale, Agnes;Gerald, William;Topal, Michael D.;Qi, Yuan;Balu, Sai;Shi, Yan;Wu, George;Bittner, Michael;Shelton, Troy;Lenkiewicz, Elizabeth;Morris, Scott;Beasley, Debbie;Sanders, Sheri;Sfeir, Robert;Chen, Jessica;Nassau, David;Feng, Larry;Hickey, Erin;Schaefer, Carl;Madhavan, Subha;Buetow, Ken;Barker, Anna;Vockley, Joseph;Compton, Carolyn;Vaught, Jim;Fielding, Peter;Collins, Francis;Good, Peter;Guyer, Mark;Ozenberger, Brad;Peterson, Jane;Thomson, Elizabeth
通讯作者：
Thomson, Elizabeth
影响因子：
5.8
作者：
Bengtsson, H.;Irizarry, R.;Speed, T. P.
通讯作者：
Speed, T. P.
影响因子：
3
作者：
Bengtsson H;Hössjer O
通讯作者：
Hössjer O