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Cell. 2017 Nov 30;171(6):1437-1452.e17. doi: 10.1016/j.cell.2017.10.049.

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

Author information

1
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
2
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA.
3
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
4
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA.
5
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
6
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. Electronic address: golub@broadinstitute.org.

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 https://clue.io.

KEYWORDS:

Functional genomics; chemical biology; gene expression profiling

PMID:
29195078
PMCID:
PMC5990023
DOI:
10.1016/j.cell.2017.10.049
[Indexed for MEDLINE]
Free PMC Article

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