A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.
A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.
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DOI：
10.1016/j.cell.2017.10.049
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发表时间：
2017-11-30
期刊：
影响因子：
64.5
通讯作者：
Golub TR
中科院分区：
文献类型：
--
作者：
Subramanian A;Narayan R;Corsello SM;Peck DD;Natoli TE;Lu X;Gould J;Davis JF;Tubelli AA;Asiedu JK;Lahr DL;Hirschman JE;Liu Z;Donahue M;Julian B;Khan M;Wadden D;Smith IC;Lam D;Liberzon A;Toder C;Bagul M;Orzechowski M;Enache OM;Piccioni F;Johnson SA;Lyons NJ;Berger AH;Shamji AF;Brooks AN;Vrcic A;Flynn C;Rosains J;Takeda DY;Hu R;Davison D;Lamb J;Ardlie K;Hogstrom L;Greenside P;Gray NS;Clemons PA;Silver S;Wu X;Zhao WN;Read-Button W;Wu X;Haggarty SJ;Ronco LV;Boehm JS;Schreiber SL;Doench JG;Bittker JA;Root DE;Wong B;Golub TR
我们之前试验了连接图（CMap）的概念，通过共同的基因表达特征将基因，药物和疾病状态连接起来。在这里，我们报告了作为NIH LINCS联盟的一部分，CMap的规模扩大了1，000倍以上，这是通过一种新的、低成本、高通量的减少代表性表达分析方法（我们称之为L1, 000）实现的。我们表明，L1000是高度可重复的，与RNA测序相当，并适合于计算推断81%的非测量转录本的表达水平。我们进一步表明，扩展的CMap可用于发现小分子的作用机制，功能注释疾病基因的遗传变异，并为临床试验提供信息。这里描述的130万个L1000配置文件及其分析工具可在https://clue.io上获得。下一代连接图是一个大规模的人类细胞功能扰动的概要，与基因表达读数相结合，有助于发现基因，药物和疾病之间的联系。
We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io. The next generation Connectivity Map, a large-scale compendium of functional perturbations in cultured human cells coupled to a gene expression read-out, facilitates the discovery of connections between genes, drugs, and diseases.
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影响因子：
46.9
作者：
Jackson, AL;Bartz, SR;Linsley, PS
通讯作者：
Linsley, PS
影响因子：
50.3
作者：
Berger AH;Brooks AN;Wu X;Shrestha Y;Chouinard C;Piccioni F;Bagul M;Kamburov A;Imielinski M;Hogstrom L;Zhu C;Yang X;Pantel S;Sakai R;Watson J;Kaplan N;Campbell JD;Singh S;Root DE;Narayan R;Natoli T;Lahr DL;Tirosh I;Tamayo P;Getz G;Wong B;Doench J;Subramanian A;Golub TR;Meyerson M;Boehm JS
通讯作者：
Boehm JS
影响因子：
4.3
作者：
Fortney K;Griesman J;Kotlyar M;Pastrello C;Angeli M;Sound-Tsao M;Jurisica I
通讯作者：
Jurisica I
DOI：
10.1073/pnas.1501597112
发表时间：
2015-10-13
影响因子：
11.1
作者：
Brum, Andrea M.;van de Peppel, Jeroen;van Leeuwen, Johannes P. T. M.
通讯作者：
van Leeuwen, Johannes P. T. M.
影响因子：
16
作者：
Hao, Bing;Oehlmann, Stephanie;Pavletich, Nikola P.
通讯作者：
Pavletich, Nikola P.