Spatial normalization of reverse phase protein array data.
Spatial normalization of reverse phase protein array data.
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DOI：
10.1371/journal.pone.0097213
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Sander C
中科院分区：
文献类型：
--
作者：
Kaushik P;Molinelli EJ;Miller ML;Wang W;Korkut A;Liu W;Ju Z;Lu Y;Mills G;Sander C
反相蛋白质阵列（RPPA）是一种高效、高通量、低成本的方法，用于复杂生物样品中特定蛋白质的定量分析。RPPA数据的质量可能受到各种错误来源的影响。其中之一，空间变异，是由RPPA载玻片的不同部分不均匀暴露于用于蛋白质检测的试剂引起的。我们提出了一种方法来确定和纠正系统的空间变化的RPPA载玻片上印刷的阳性控制点。该方法使用一种简单的双线性插值技术来获得一个表面，表示发生在滑动尺寸上的空间变化。该表面用于计算校正因子，校正因子可以使每个载玻片上样品的相对蛋白质浓度归一化。该方法的采用增加了各种肿瘤和细胞系衍生样品的技术和生物复制之间的一致性。此外，在一项黑色素瘤细胞系SKMEL-133的研究数据中，由于变异系数（CV）大于15%而被拒绝的几个载玻片，在每个病例中都通过将CV降低到这个阈值以下而获救。该方法是用R统计编程语言实现的。它与RPPA数据分析中常用的MicroVigene和SuperCurve包兼容。该方法以及实施建议可在http://bitbucket.org/rppa_preprocess/rppa_preprocess/src上获得。
Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src.
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影响因子：
5.1
作者：
Strosznajder, RP;Jesko, H;Zambrzycka, A
通讯作者：
Zambrzycka, A
影响因子：
3.7
作者：
Troncale S;Barbet A;Coulibaly L;Henry E;He B;Barillot E;Dubois T;Hupé P;de Koning L
通讯作者：
de Koning L
影响因子：
2
作者：
Neeley ES;Baggerly KA;Kornblau SM
通讯作者：
Kornblau SM
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：
7.3
作者：
Gulmann, Christian;Sheehan, Katherine M.;Petricoin, Emanuel F., III
通讯作者：
Petricoin, Emanuel F., III