作者
Aravind Subramanian, Rajiv Narayan, Steven M Corsello, David D Peck, Ted E Natoli, Xiaodong Lu, Joshua Gould, John F Davis, Andrew A Tubelli, Jacob K Asiedu, David L Lahr, Jodi E Hirschman, Zihan Liu, Melanie Donahue, Bina Julian, Mariya Khan, David Wadden, Ian C Smith, Daniel Lam, Arthur Liberzon, Courtney Toder, Mukta Bagul, Marek Orzechowski, Oana M Enache, Federica Piccioni, Sarah A Johnson, Nicholas J Lyons, Alice H Berger, Alykhan F Shamji, Angela N Brooks, Anita Vrcic, Corey Flynn, Jacqueline Rosains, David Y Takeda, Roger Hu, Desiree Davison, Justin Lamb, Kristin Ardlie, Larson Hogstrom, Peyton Greenside, Nathanael S Gray, Paul A Clemons, Serena Silver, Xiaoyun Wu, Wen-Ning Zhao, Willis Read-Button, Xiaohua Wu, Stephen J Haggarty, Lucienne V Ronco, Jesse S Boehm, Stuart L Schreiber, John G Doench, Joshua A Bittker, David E Root, Bang Wong, Todd R Golub
发表日期
2017/11/30
期刊
Cell
卷号
171
期号
6
页码范围
1437-1452. e17
出版商
Elsevier
简介
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.
学术搜索中的文章
A Subramanian, R Narayan, SM Corsello, DD Peck… - Cell, 2017