A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

Cell

Authors	Aravind Subramanian Rajiv Narayan Steven Corsello David Peck Ted Natoli Xiaodong Lu Joshua Gould John Davis Andrew Tubelli Jacob Asiedu David Lahr Jodi Hirschman Zihan Liu Melanie Donahue Bina Julian Mariya Khan David Wadden Ian Smith Daniel Lam Arthur Liberzon Courtney Toder Mukta Bagul Marek Orzechowski Oana Enache Federica Piccioni Sarah Johnson Nicholas Lyons Alice Berger Alykhan Shamji Angela Brooks Anita Vrcic Corey Flynn Jacqueline Rosains David Takeda Roger Hu Desiree Davison Justin Lamb Kristin Ardlie Larson Hogstrom Peyton Greenside Nathanael Gray Paul Clemons Serena Silver Xiaoyun Wu Wen-Ning Zhao Willis Read-Button Xiaohua Wu Stephen Haggarty Lucienne Ronco Jesse Boehm Stuart Schreiber John Doench Joshua Bittker David Root Bang Wong Todd Golub
Keywords	Humans Gene Expression Profiling Neoplasms Organ Specificity Cell Line, Tumor Sequence Analysis, RNA Drug Resistance, Neoplasm Small Molecule Libraries Pharmaceutical Preparations
Abstract	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 .
Year of Publication	2017
Journal	Cell
Volume	171
Issue	6
Pages	1437-1452.e17
Date Published	2017 Nov 30
ISSN	1097-4172
DOI	10.1016/j.cell.2017.10.049
PubMed ID	29195078
PubMed Central ID	PMC5990023
Links
Grant list	KL2 TR001100 / TR / NCATS NIH HHS / United States U54 HG006093 / HG / NHGRI NIH HHS / United States T32 CA009172 / CA / NCI NIH HHS / United States U01 HG008699 / HG / NHGRI NIH HHS / United States U54 HL127366 / HL / NHLBI NIH HHS / United States