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R/data.R
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R/data.R
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#' Dataset with 420 antibiotics
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#'
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#' A dataset containing all antibiotics with a J0 code, with their DDD's. Properties were downloaded from the WHO, see Source.
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#' @format A data.frame with 420 observations and 16 variables:
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#' @format A data.frame with 420 observations and 18 variables:
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#' \describe{
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#' \item{\code{atc}}{ATC code, like \code{J01CR02}}
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#' \item{\code{molis}}{MOLIS code, like \code{amcl}}
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#' Dataset with ~2500 microorganisms
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#'
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#' A dataset containing 2500 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
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#' @format A data.frame with 2507 observations and 12 variables:
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#' A dataset containing 2453 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
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#' @format A data.frame with 2453 observations and 12 variables:
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#' \describe{
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#' \item{\code{bactid}}{ID of microorganism}
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#' \item{\code{bactsys}}{Bactsyscode of microorganism}
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README.md
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README.md
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# `AMR`
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This is an [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR).
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### An [R package](https://www.r-project.org) to simplify the analysis and prediction of Antimicrobial Resistance (AMR).
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[![logo_rug](man/figures/logo_rug.png)](https://www.rug.nl)[![logo_umcg](man/figures/logo_umcg.png)](https://www.umcg.nl)[![logo_eh1h](man/figures/logo_eh1h.png)](http://www.eurhealth-1health.eu)[![logo_interreg](man/figures/logo_interreg.png)](http://www.eurhealth-1health.eu)
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[![logo_rug](man/figures/logo_rug.png)](https://www.rug.nl)[![logo_umcg](man/figures/logo_umcg.png)](https://www.umcg.nl)
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This R package was created for academic research by PhD students of the Faculty of Medical Sciences of the [University of Groningen)](https://www.rug.nl) and the Medical Microbiology & Infection Prevention department of the [University Medical Center Groningen (UMCG)](https://www.umcg.nl). They also maintain this package, see [Authors](#authors).
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This R package was created for academic research by PhD students of the Faculty of Medical Sciences of the [University of Groningen)](https://www.rug.nl) and the Medical Microbiology & Infection Prevention (MMBI) department of the [University Medical Center Groningen (UMCG)](https://www.umcg.nl). See [Authors](#authors).
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## Why this package?
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This R package contains functions to make microbiological, epidemiological data analysis easier. It allows the use of some new classes to work with MIC values and antimicrobial interpretations (i.e. values S, I and R).
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This R package contains functions to make **microbiological, epidemiological data analysis easier**. It allows the use of some new classes to work with MIC values and antimicrobial interpretations (i.e. values S, I and R).
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With `AMR` you can also:
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* Create frequency tables with the `freq` function
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### Databases included in package
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Datasets to work with antibiotics and bacteria properties.
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```r
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# Dataset with ATC antibiotics codes, official names and DDD's (oral and parenteral)
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ablist # A tibble: 420 x 12
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# Dataset with 2000 random blood culture isolates from anonymised septic patients between 2001 and 2017 in 5 Dutch hospitals
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septic_patients # A tibble: 4,000 x 47
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# Dataset with ATC antibiotics codes, official names, trade names and DDD's (oral and parenteral)
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antibiotics # A tibble: 420 x 18
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# Dataset with bacteria codes and properties like gram stain and aerobic/anaerobic
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bactlist # A tibble: 2,507 x 10
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microorganisms # A tibble: 2,453 x 12
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```
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<sup>2</sup> Certe Medical Diagnostics & Advice, Groningen, the Netherlands
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[![logo_umcg](man/figures/logo_umcg.png)](https://www.umcg.nl)[![logo_certe](man/figures/logo_certe.png)](https://www.certe.nl)[![logo_eh1h](man/figures/logo_eh1h.png)](http://www.eurhealth-1health.eu)[![logo_interreg](man/figures/logo_interreg.png)](http://www.eurhealth-1health.eu)
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## Copyright
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[![License](https://img.shields.io/github/license/msberends/AMR.svg?colorB=3679BC)](https://github.com/msberends/AMR/blob/master/LICENSE)
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\name{antibiotics}
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\alias{antibiotics}
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\title{Dataset with 420 antibiotics}
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\format{A data.frame with 420 observations and 16 variables:
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\format{A data.frame with 420 observations and 18 variables:
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\describe{
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\item{\code{atc}}{ATC code, like \code{J01CR02}}
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\item{\code{molis}}{MOLIS code, like \code{amcl}}
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\name{microorganisms}
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\alias{microorganisms}
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\title{Dataset with ~2500 microorganisms}
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\format{A data.frame with 2507 observations and 12 variables:
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\format{A data.frame with 2453 observations and 12 variables:
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\describe{
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\item{\code{bactid}}{ID of microorganism}
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\item{\code{bactsys}}{Bactsyscode of microorganism}
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microorganisms
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}
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\description{
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A dataset containing 2500 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
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A dataset containing 2453 microorganisms. MO codes of the UMCG can be looked up using \code{\link{microorganisms.umcg}}.
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}
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\seealso{
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\code{\link{guess_bactid}} \code{\link{antibiotics}} \code{\link{microorganisms.umcg}}
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