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63 lines
4.2 KiB
R
63 lines
4.2 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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#' The `AMR` Package
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#'
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#' Welcome to the `AMR` package.
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#' @details
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#' `AMR` is a free and open-source R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods. It supports any table format, including WHONET/EARS-Net data.
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#'
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#' We created this package for both academic research and routine analysis at the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG). This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.
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#'
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#' This package can be used for:
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#' - Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the [Catalogue of Life](http://www.catalogueoflife.org)
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#' - Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines
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#' - Determining first isolates to be used for AMR analysis
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#' - Calculating antimicrobial resistance
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#' - Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO)
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#' - Calculating (empirical) susceptibility of both mono therapy and combination therapies
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#' - Predicting future antimicrobial resistance using regression models
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#' - Getting properties for any microorganism (like Gram stain, species, genus or family)
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#' - Getting properties for any antibiotic (like name, EARS-Net code, ATC code, PubChem code, defined daily dose or trade name)
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#' - Plotting antimicrobial resistance
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#' - Applying EUCAST expert rules
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#' @section Read more on our website!:
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#' On our website <https://msberends.gitlab.io/AMR> you can find [a tutorial](https://msberends.gitlab.io/AMR/articles/AMR.html) about how to conduct AMR analysis, the [complete documentation of all functions](https://msberends.gitlab.io/AMR/reference) (which reads a lot easier than here in R) and [an example analysis using WHONET data](https://msberends.gitlab.io/AMR/articles/WHONET.html).
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#' @section Contact us:
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#' For suggestions, comments or questions, please contact us at:
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#'
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#' Matthijs S. Berends \cr
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#' m.s.berends at umcg dot nl \cr
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#' Department of Medical Microbiology, University of Groningen \cr
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#' University Medical Center Groningen \cr
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#' Post Office Box 30001 \cr
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#' 9700 RB Groningen \cr
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#' The Netherlands
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#'
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#' If you have found a bug, please file a new issue at: \cr
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#' <https://gitlab.com/msberends/AMR/issues>
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#' @name AMR
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#' @rdname AMR
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#' @importFrom microbenchmark microbenchmark
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#' @importFrom knitr kable
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NULL
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