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Cell DOI:10.1016/j.cell.2017.10.049

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

Publication TypeJournal Article
Year of Publication2017
AuthorsSubramanian, 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, W-N, Read-Button, W, Wu, X, Haggarty, SJ, Ronco, LV, Boehm, JS, Schreiber, SL, Doench, JG, Bittker, JA, Root, DE, Wong, B, Golub, TR
Date Published2017 Nov 30
KeywordsCell Line, Tumor, Drug Resistance, Neoplasm, Gene Expression Profiling, Humans, Neoplasms, Organ Specificity, Pharmaceutical Preparations, Sequence Analysis, RNA, Small Molecule Libraries

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


Alternate JournalCell
PubMed ID29195078
PubMed Central IDPMC5990023
Grant ListKL2 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