mirror of https://github.com/msberends/AMR.git
183 lines
6.9 KiB
Markdown
183 lines
6.9 KiB
Markdown
# `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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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). They also maintain this package, 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 S3 classes to work with MIC values and antimicrobial interpretations (i.e. values S, I and R).
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AMR can also be predicted for the forthcoming years with the `rsi_predict` function. For use with the `dplyr` package, the `rsi` function can be used in conjunction with `summarise` to calculate the resistance percentages of different antibiotic columns of a table.
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It also contains functions to translate antibiotic codes from the lab (like `"AMOX"`) or the [WHO](https://www.whocc.no/atc_ddd_index/?code=J01CA04&showdescription=no) (like `"J01CA04"`) to trivial names (like `"amoxicillin"`) and vice versa.
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## How to get it?
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This package is available on CRAN and also here on GitHub.
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### From CRAN (recommended, latest stable version)
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[](http://cran.r-project.org/package=AMR)
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[](http://cran.r-project.org/package=AMR)
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- RStudio:
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- Click on `Tools` and then `Install Packages...`
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- Type in `AMR` and press <kbd>Install</kbd>
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- R console:
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- `install.packages("AMR")`
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### From GitHub (latest development version)
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[](https://travis-ci.org/msberends/AMR)
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[](https://github.com/msberends/AMR/releases)
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[](https://github.com/msberends/AMR/commits/master)
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```r
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install.packages("devtools")
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devtools::install_github("msberends/AMR")
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```
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## How to use it?
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```r
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# Call it with:
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library(AMR)
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# For a list of functions:
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help(package = "AMR")
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```
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### Overwrite/force resistance based on EUCAST rules
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This is also called *interpretive reading*.
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```r
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before <- data.frame(bactid = c("STAAUR", # Staphylococcus aureus
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"ENCFAE", # Enterococcus faecalis
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"ESCCOL", # Escherichia coli
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"KLEPNE", # Klebsiella pneumoniae
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"PSEAER"), # Pseudomonas aeruginosa
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vanc = "-", # Vancomycin
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amox = "-", # Amoxicillin
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coli = "-", # Colistin
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cfta = "-", # Ceftazidime
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cfur = "-", # Cefuroxime
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stringsAsFactors = FALSE)
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before
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# bactid vanc amox coli cfta cfur
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# 1 STAAUR - - - - -
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# 2 ENCFAE - - - - -
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# 3 ESCCOL - - - - -
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# 4 KLEPNE - - - - -
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# 5 PSEAER - - - - -
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# Now apply those rules; just need a column with bacteria ID's and antibiotic results:
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after <- EUCAST_rules(before)
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after
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# bactid vanc amox coli cfta cfur
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# 1 STAAUR - - R R -
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# 2 ENCFAE - - R R R
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# 3 ESCCOL R - - - -
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# 4 KLEPNE R R - - -
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# 5 PSEAER R R - - R
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```
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### New classes
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This package contains two new S3 classes: `mic` for MIC values (e.g. from Vitek or Phoenix) and `rsi` for antimicrobial drug interpretations (i.e. S, I and R). Both are actually ordered factors under the hood (an MIC of `2` being higher than `<=1` but lower than `>=32`, and for class `rsi` factors are ordered as `S < I < R`).
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Both classes have extensions for existing generic functions like `print`, `summary` and `plot`.
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```r
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# Transform values to new classes
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mic_data <- as.mic(c(">=32", "1.0", "8", "<=0.128", "8", "16", "16"))
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rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
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```
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These functions also try to coerce valid values.
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Quick overviews when just printing objects:
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```r
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mic_data
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# Class 'mic': 7 isolates
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#
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# <NA> 0
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#
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# <=0.128 1 8 16 >=32
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# 1 1 2 2 1
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rsi_data
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# Class 'rsi': 880 isolates
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#
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# <NA>: 0
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# Sum of S: 474
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# Sum of IR: 406
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# - Sum of R: 370
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# - Sum of I: 36
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#
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# %S %IR %I %R
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# 53.9 46.1 4.1 42.0
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```
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A plot of `rsi_data`:
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```r
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plot(rsi_data)
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```
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Other epidemiological functions:
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```r
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# Determine key antibiotic based on bacteria ID
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key_antibiotics(...)
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# Selection of first isolates of any patient
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first_isolate(...)
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# Calculate resistance levels of antibiotics, can be used with `summarise` (dplyr)
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rsi(...)
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# Predict resistance levels of antibiotics
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rsi_predict(...)
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# Get name of antibiotic by ATC code
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abname(...)
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abname("J01CR02", from = "atc", to = "umcg") # "AMCL"
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```
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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 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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```
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## Authors
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- [Berends MS](https://github.com/msberends)<sup>1,2</sup>, PhD Student
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- [Luz CF](https://github.com/ceefluz)<sup>1</sup>, PhD Student
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- [Hassing EEA](https://github.com/erwinhassing)<sup>2</sup>, Data Analyst (contributor)
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<sup>1</sup> Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
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<sup>2</sup> Department of Medical, Market and Innovation (MMI), Certe Medische diagnostiek & advies, Groningen, the Netherlands
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## Copyright
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[](https://github.com/msberends/AMR/blob/master/LICENSE)
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This R package is licensed under the [GNU General Public License (GPL) v2.0](https://github.com/msberends/AMR/blob/master/LICENSE). In a nutshell, this means that this package:
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- May be used for commercial purposes
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- May be used for private purposes
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- May be modified, although:
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- Modifications **must** be released under the same license when distributing the package
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- Changes made to the code **must** be documented
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- May be distributed, although:
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- Source code **must** be made available when the package is distributed
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- A copy of the license and copyright notice **must** be included with the package.
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- Comes with a LIMITATION of liability
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- Comes with NO warranty
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