Menu |
Connectivity Map

Unravel biology with the world’s largest perturbation-driven gene expression dataset.


We are creating a genome-scale library of cellular signatures that catalogs transcriptional responses to chemical, genetic, and disease perturbation. To date, the library contains 1,800,255 profiles resulting from perturbations of multiple cell types.


CMap is a resource that uses gene expression signatures to probe relationships between diseases, cell physiology, and therapeutics. The patterns of gene expression (a "signature") that arise from a disease, genetic perturbation (knockdown or overexpression of a gene) or treatment with a small molecule compound are compared for similarity to all perturbational signatures in the database. Perturbagens that give rise to highly similar (or opposing) expression signatures are "connected" and thus may have related effects on the cell. Our goal is to use these connections to uncover novel treatments for a variety of diseases, including cancers, neurological diseases, and infectious diseases.


The data is a massive catalog of gene expression profiles representing transcriptional responses to a wide variety of chemical, genetic and disease perturbations.


Big data sets can be an enigmatic monolith without the proper interface to access and interpret the information they hold. We offer command line interfaces (CLI) for computational biologists, API's for software engineers, and web-based software applications for all. Check out our collection of Web Apps and Developer's Tools.


  • Berger AH, Brooks AN, Wu X, Shrestha Y, Chouinard C, Piccioni F, Bagul M, Kamburov A, Imielinski M, Hogstrom L, et al. High-throughput Phenotyping of Lung Cancer Somatic Mutations. Cancer Cell. 2016/08/08. 30(2):214-28, (2016). 
  • Chen Y, Li Y, Narayan R, Subramanian A, Xie X. Gene expression inference with deep learning. Bioinformatics. 2016/06/15. 32(12):1832-9, (2016). 
  • Duan Q, Flynn C, Niepel M, Hafner M, Muhlich JL, Fernandez NF, Rouilard AD, Tan CM, Chen EY, Golub TR, Sorger PK, Subramanian A, Ma'ayan A. LINCS Canvas Browser: interactive web app to query, browse, and interrogate LINCS L1000 gene expression signatures. Nucleic Acids Research. 2014/6/06. 42(Web Server Issue):W449-60, (2014). 
  • Johannessen CM, Johnson LA, Piccioni F, Townes A, Frederick DT, Donahue MK, Narayan R, Flaherty KT, Wargo JA, Root DE, Garraway LA. A melanocyte lineage program confers resistance to MAP kinase pathway inhibition. Nature. 2013/12/5. 504(7478):138-42, (2013). 
  • Kim E, Ilic N, Shrestha Y, Zou L, Kamburov A, Zhu C, Lubonja R, Tran N, Nguyen C, Lawrence MS, et al. Systematic Functional Interrogation of Rare Cancer Variants Identifies Oncogenic Alleles. Cancer Discovery. 2016/05/04. 6(6), (2014). 
  • Lamb J, Crawford ED, Peck D, Modell JW, Blat IC, Wrobel MJ, Lerner J, Brunet JP, Subramanian A, Ross KN, et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 2006/9/29. 313(5795):1929-35, (2006). 
  • Liberzon A, Subramanian A, Pinchback R, Thorvaldsdóttir H, Tamayo P, Mesirov JP. Molecular signatures database (MSigDB) 3.0. Bioinformatics. 2011/06/15. 27(12):1739-20, (2011). 
  • Peck D, Crawford ED, Ross KN, Stegmaier K, Golub TR, Lamb J. A method for high-throughput gene expression signature analysis. Genome Biology. 2006/07/19. 7(7):R61, (2006). 
  • Santagata S, Mendillo ML, Tang YC, Subramanian A, Perley CC, Roche SP, Wong B, Narayan R, Kwon H, Koeva M, Amon A, Golub TR, Porco JA Jr., Whitesell L,Lindquist S. Tight coordination of protein translation and HSF1 activation supports the anabolic malignant state. Science. 2013/7/19. 341(6143), (2013). 
  • Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences. 2005/10/25. 102(43):15545-50, (2005). 
  • Wilson FH, Johannessen CM, Piccioni F, Tamayo P, Kim JW, Van Allen EM, Corsello SM, Capelletti M, Calles A, Butaney M, et al. A functional landscape of resistance to ALK inhibition in lung cancer. Cancer Cell. 2015/05/27. 27(3):397-408, (2015). 


We are grateful for the important contributions from the Broad community, the CMap Team, our research collaborators, and third party code developers.  

Contact CMap