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Journal Article

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

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

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
Journal Name
Publication Date
November, 2017