MultiAssayExperiment specifications


Unique identifier OMICS_19308
Name MultiAssayExperiment
Software type Framework/Library, Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License Artistic License version 2.0
Computer skills Advanced
Version 1.2.1
Stability Stable
Maintained Yes



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  • person_outline Levi Waldron <>
  • person_outline Marcel Ramos <>

Additional information

Publication for MultiAssayExperiment

MultiAssayExperiment institution(s)
CUNY School of Public Health, New York, NY, USA; Institute for Implementation Science in Population Health, City University of New York, NY, USA; Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Polo Scientifico e Tecnologico Fabio Ferrari, Trento, Italy; Harvard TH Chan School of Public Health, Boston, MA, USA; Computational Biology Support Team, Cancer Research UK Manchester Institute, The University of Manchester, Manchester, UK; Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Mucosal and Salivary Biology Division, King's College London Dental Institute, London, UK; Dana-Farber Cancer Institute, Boston, MA, USA; Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Department of Computer Science, University of Toronto, Toronto, ON, Canada; Ontario Institute of Cancer Research, Toronto, ON, Canada; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA; Novartis Institutes for BioMedical Research, Cambridge, MA, USA; Roswell Park Cancer Institute, University of Buffalo, Buffalo, New York, NY, USA; Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
MultiAssayExperiment funding source(s)
Supported by the National Cancer Institute of the National Institutes of Health [U24CA180996]; by the CUNY High Performance Computing Center, which is operated by the College of Staten Island and funded, in part, by grants from the City of New York, State of New York, CUNY Research Foundation, and National Science Foundation Grants CNS-0958379, CNS-0855217 and ACI 1126113.

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