PAIRUP-MS statistics

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Popular tool citations

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Associated diseases

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PAIRUP-MS specifications

Information


Unique identifier OMICS_23650
Name PAIRUP-MS
Alternative name Pathway Analysis and Imputation to Relate Unknowns in Profiles from MS-based metabolite data
Software type Framework/Library
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python, R, Shell (Bash)
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Requirements
ROCR, python, ggplot2 2.2.1, scipy 0.16.0 0.16.0, scipy 0.16.0, pairup, ggplot2 2.2.1 2.2.1, pairup-ms
Maintained Yes

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Maintainers


  • person_outline Yu-Han Hsu <>
  • person_outline Joel Hirschhorn <>

Publication for Pathway Analysis and Imputation to Relate Unknowns in Profiles from MS-based metabolite data

PAIRUP-MS institution(s)
Department of Genetics, Harvard Medical School, Boston, MA, USA; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children’s Hospital, Boston, MA, USA; Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Analytical and Translational Genomics Unit, Massachusetts General Hospital, Boston, MA, USA; Novo Nordisk Foundation Centre for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark; Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark; Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Estonian Genome Center, University of Tartu, Tartu, Estonia; BioAge Labs, Richmond, CA, USA; Instituto Nacional de Salud Publica, Cuernavaca, Morelos, Mexico; Centro de Estudios en Diabetes, Mexico City, Mexico
PAIRUP-MS funding source(s)
Supported by grants from the National Heart, Lung, and Blood Institute (F31HL126581), National Institute of Diabetes and Digestive and Kidney Diseases (R01DK075787), Doris Duke Charitable Foundation (215205), Estonian Research Council (IUT20-60, PUT1665, PUT1660), European Union through Horizon 2020 (692145), and European Union through the European Regional Development Fund (Project N. 2014-2020.4.01.15-0012).

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