RASE prediction pipeline specifications

Information


Unique identifier OMICS_31651
Name RASE prediction pipeline
Alternative name Resistance Associated Sequence Elements prediction pipeline
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use None
Biological technology Oxford Nanopore
Operating system Unix/Linux
Programming languages Python, R, Shell (Bash)
License MIT License
Computer skills Advanced
Stability Stable
Requirements
prophyle, ete, pysam, snakemake
Maintained Yes

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Versioning


No version available

Documentation


Maintainer


  • person_outline Karel Břinda

Publication for Resistance Associated Sequence Elements prediction pipeline

RASE prediction pipeline institution(s)
Center for Communicable Disease Dynamic, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; University of East Anglia, Norwich Research Park, Norwich, UK; Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, ON, Canada; CNRS/LIGM Université Paris-Est, Marne-la-Vallée, France; Skolkovo Institute of Science and Technology, Moscow, Russia; Quadram Institute Bioscience, Norwich Research Park, Norwich, UK; Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA
RASE prediction pipeline funding source(s)
Supported by the Bill & Melinda Gates Foundation (GCGH GCE OPP1151010), NIH-National Institute of Allergy and Infectious Diseases (R01 AI106786-05), the Canadian Institutes of Health Research (FRN 152448), the Canadian Institutes for Health Research (a fellowship grant), the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Reference Number RP-PG-0514-20018), the UK Antimicrobial Resistance Cross Council Initiative (MR/N013956/1), Rosetrees Trust (A749), the University of East Anglia, and Oxford Nanopore Technologies.

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