mirror of https://github.com/msberends/AMR.git
59 lines
3.5 KiB
Plaintext
59 lines
3.5 KiB
Plaintext
---
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title: "Welcome to the AMR package"
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author: "Matthijs S. Berends"
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date: '`r format(Sys.Date(), "%d %B %Y")`'
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output:
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rmarkdown::html_vignette:
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toc: true
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toc_depth: 3
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vignette: >
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%\VignetteIndexEntry{Welcome to the AMR package}
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%\VignetteEncoding{UTF-8}
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%\VignetteEngine{knitr::rmarkdown}
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editor_options:
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chunk_output_type: console
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---
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```{r setup, include = FALSE, results = 'markup'}
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knitr::opts_chunk$set(
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warning = FALSE,
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collapse = TRUE,
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comment = "#",
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fig.width = 7.5,
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fig.height = 5
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)
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```
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**READ ALL VIGNETTES [ON OUR WEBSITE](https://msberends.github.io/AMR/articles/).**
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# Welcome to the AMR package
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`AMR` is a free, open-source and independent R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible antimicrobial resistance data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
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After installing this package, R knows **~70,000 distinct microbial species** and all **~550 antibiotic, antimycotic and antiviral drugs** by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
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This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained (see Changelog) and is free software (see Copyright).
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Since its first public release in early 2018, this package has been downloaded from more than 100 countries.
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## Usage examples
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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 and List of Prokaryotic names with Standing in Nomenclature
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* Interpreting raw MIC and disk diffusion values, based on the latest CLSI or EUCAST guidelines
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* Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records
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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, code of EARS-Net/ATC/LOINC/PubChem, 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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* Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code
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* Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code
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* Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI
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* Principal component analysis for AMR
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