Genome Modeling System: A Knowledge Management Platform for Genomics.
Genome Modeling System: A Knowledge Management Platform for Genomics.
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DOI：
10.1371/journal.pcbi.1004274
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发表时间：
2015-07
影响因子：
4.3
通讯作者：
Wilson RK
中科院分区：
文献类型：
--
作者：
Griffith M;Griffith OL;Smith SM;Ramu A;Callaway MB;Brummett AM;Kiwala MJ;Coffman AC;Regier AA;Oberkfell BJ;Sanderson GE;Mooney TP;Nutter NG;Belter EA;Du F;Long RL;Abbott TE;Ferguson IT;Morton DL;Burnett MM;Weible JV;Peck JB;Dukes A;McMichael JF;Lolofie JT;Derickson BR;Hundal J;Skidmore ZL;Ainscough BJ;Dees ND;Schierding WS;Kandoth C;Kim KH;Lu C;Harris CC;Maher N;Maher CA;Magrini VJ;Abbott BS;Chen K;Clark E;Das I;Fan X;Hawkins AE;Hepler TG;Wylie TN;Leonard SM;Schroeder WE;Shi X;Carmichael LK;Weil MR;Wohlstadter RW;Stiehr G;McLellan MD;Pohl CS;Miller CA;Koboldt DC;Walker JR;Eldred JM;Larson DE;Dooling DJ;Ding L;Mardis ER;Wilson RK
在这项工作中，我们介绍了基因组建模系统（GMS），这是一个能够大规模执行自动化基因组分析流程的分析信息管理系统。GMS框架提供了对样本和数据的详细追踪，以及可靠且可重复的分析流程。GMS还可作为生物信息学开发的平台，允许大型团队在数据分析上进行协作，或者单个研究人员在其数据管理系统内有效地利用他人的工作成果。GMS并非将临时分析与严格的、可重复的流程分离开来，而是促进了两者之间的系统性整合。作为对GMS的演示，我们对来自一种乳腺癌细胞系（HCC1395）和匹配的淋巴母细胞系（HCC1395BL）的全基因组、外显子组和转录组测序数据进行了综合分析。这些数据可供用户测试软件、完成教程以及开发新的GMS流程配置。GMS可在https://github.com/genome/gms获取。
In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.
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影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.1038/nrc1299
发表时间：
2004-03
期刊：
Nature reviews. Cancer
影响因子：
--
作者：
通讯作者：
--
影响因子：
14.9
作者：
Forbes SA;Bindal N;Bamford S;Cole C;Kok CY;Beare D;Jia M;Shepherd R;Leung K;Menzies A;Teague JW;Campbell PJ;Stratton MR;Futreal PA
通讯作者：
Futreal PA
影响因子：
64.5
作者：
Govindan R;Ding L;Griffith M;Subramanian J;Dees ND;Kanchi KL;Maher CA;Fulton R;Fulton L;Wallis J;Chen K;Walker J;McDonald S;Bose R;Ornitz D;Xiong D;You M;Dooling DJ;Watson M;Mardis ER;Wilson RK
通讯作者：
Wilson RK
影响因子：
64.8
作者：
Ley, Timothy J.;Mardis, Elaine R.;Ding, Li;Fulton, Bob;McLellan, Michael D.;Chen, Ken;Dooling, David;Dunford-Shore, Brian H.;McGrath, Sean;Hickenbotham, Matthew;Cook, Lisa;Abbott, Rachel;Larson, David E.;Koboldt, Dan C.;Pohl, Craig;Smith, Scott;Hawkins, Amy;Abbott, Scott;Locke, Devin;Hillier, LaDeana W.;Miner, Tracie;Fulton, Lucinda;Magrini, Vincent;Wylie, Todd;Glasscock, Jarret;Conyers, Joshua;Sander, Nathan;Shi, Xiaoqi;Osborne, John R.;Minx, Patrick;Gordon, David;Chinwalla, Asif;Zhao, Yu;Ries, Rhonda E.;Payton, Jacqueline E.;Westervelt, Peter;Tomasson, Michael H.;Watson, Mark;Baty, Jack;Ivanovich, Jennifer;Heath, Sharon;Shannon, William D.;Nagarajan, Rakesh;Walter, Matthew J.;Link, Daniel C.;Graubert, Timothy A.;DiPersio, John F.;Wilson, Richard K.
通讯作者：
Wilson, Richard K.