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<!-- index.md is generated from index.Rmd; please edit that file. -->
# The `AMR` Package for R <a href="https://amr-for-r.org/"><img src="./logo.svg" align="right" height="139" /></a>
* Provides an **all-in-one solution** for antimicrobial resistance (AMR) data analysis in a One Health approach
* Peer-reviewed, used in over 175 countries, available in 20 languages
* Generates **antibiograms** - traditional, combined, syndromic, and even WISCA
* Provides the **full microbiological taxonomy** and extensive info on **all antimicrobial drugs**
* Applies all recent **CLSI** and **EUCAST** clinical and veterinary breakpoints for MICs, disk zones and ECOFFs
* Corrects for duplicate isolates, **calculates** and **predicts** AMR per antimicrobial class
* Integrates with **WHONET**, ATC, **EARS-Net**, PubChem, **LOINC**, **SNOMED CT**, and **NCBI**
* 100% free of costs and dependencies, highly suitable for places with **limited resources**
- Provides an **all-in-one solution** for antimicrobial resistance (AMR)
data analysis in a One Health approach
- Peer-reviewed, used in over 175 countries, available in 20 languages
- Generates **antibiograms** - traditional, combined, syndromic, and
even WISCA
- Provides the **full microbiological taxonomy** of ~79 000 distinct
species and extensive info of ~620 antimicrobial drugs
- Applies **CLSI 2011-2025** and **EUCAST 2011-2025** clinical and
veterinary breakpoints, and ECOFFs, for MIC and disk zone
interpretation
- Corrects for duplicate isolates, **calculates** and **predicts** AMR
per antimicrobial class
- Integrates with **WHONET**, ATC, **EARS-Net**, PubChem, **LOINC**,
**SNOMED CT**, and **NCBI**
- 100% free of costs and dependencies, highly suitable for places with
**limited resources**
> Now available for Python too! [Click here](./articles/AMR_for_Python.html) to read more.
> Now available for Python too! [Click
> here](./articles/AMR_for_Python.html) to read more.
<div style="display: flex; font-size: 0.8em;">
<p style="text-align:left; width: 50%;"><small><a href="https://amr-for-r.org/">https://amr-for-r.org</a></small></p>
<p style="text-align:right; width: 50%;"><small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank">https://doi.org/10.18637/jss.v104.i03</a></small></p>
<p style="text-align:left; width: 50%;">
<small><a href="https://amr-for-r.org/">https://amr-for-r.org</a></small>
</p>
<p style="text-align:right; width: 50%;">
<small><a href="https://doi.org/10.18637/jss.v104.i03" target="_blank">https://doi.org/10.18637/jss.v104.i03</a></small>
</p>
</div>
<a href="./reference/clinical_breakpoints.html#response-from-clsi-and-eucast"><img src="./endorsement_clsi_eucast.jpg" class="endorse_img" align="right" height="120" /></a>
----
------------------------------------------------------------------------
### Introduction
The `AMR` package is a peer-reviewed, [free and open-source](#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) 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 AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. We are a team of [many different researchers](./authors.html) from around the globe to make this a successful and durable project!
The `AMR` package is a peer-reviewed, [free and open-source](#copyright)
R package with [zero
dependencies](https://en.wikipedia.org/wiki/Dependency_hell) 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 AMR data analysis, that can therefore empower
epidemiological analyses to continuously enable surveillance and
treatment evaluation in any setting. We are a team of [many different
researchers](./authors.html) from around the globe to make this a
successful and durable project!
This work was published in the Journal of Statistical Software (Volume 104(3); [DOI 10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)) and formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)).
This work was published in the Journal of Statistical Software (Volume
104(3); [DOI
10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)) and
formed the basis of two PhD theses ([DOI
10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and
[DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)).
After installing this package, R knows [**~79,000 distinct microbial species**](./reference/microorganisms.html) (updated June 2024) and all [**~620 antimicrobial and antiviral drugs**](./reference/antimicrobials.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (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](https://www.rug.nl), in collaboration with non-profit organisations [Certe Medical Diagnostics and Advice Foundation](https://www.certe.nl) and [University Medical Center Groningen](https://www.umcg.nl).
After installing this package, R knows [**~79 000 distinct microbial
species**](./reference/microorganisms.html) (updated June 2024) and all
[**~620 antimicrobial and antiviral
drugs**](./reference/antimicrobials.html) by name and code (including
ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all
about valid SIR and MIC values. The integral clinical breakpoint
guidelines from CLSI 2011-2025 and EUCAST 2011-2025 are included, even
with epidemiological cut-off (ECOFF) values. It supports and can read
any data format, including WHONET data. This package works on Windows,
macOS and Linux with all versions of R since R-3.0 (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](https://www.rug.nl) and the [University Medical Center
Groningen](https://www.umcg.nl).
##### Used in over 175 countries, available in 20 languages
<a href="./countries_large.png" target="_blank"><img src="./countries.png" align="right" style="max-width: 300px;" /></a>
Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.
Since its first public release in early 2018, this R package has been
used in almost all countries in the world. Click the map to enlarge and
to see the country names.
With the help of contributors from all corners of the world, the `AMR` package is available in <img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> English, <img src="lang_cs.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Czech, <img src="lang_zh.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Chinese, <img src="lang_da.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Danish, <img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Dutch, <img src="lang_fi.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Finnish, <img src="lang_fr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> French, <img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> German, <img src="lang_el.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Greek, <img src="lang_it.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Italian, <img src="lang_ja.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Japanese, <img src="lang_no.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Norwegian, <img src="lang_pl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Polish, <img src="lang_pt.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Portuguese, <img src="lang_ro.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Romanian, <img src="lang_ru.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Russian, <img src="lang_es.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Spanish, <img src="lang_sv.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Swedish, <img src="lang_tr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Turkish, and <img src="lang_uk.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;"> Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
With the help of contributors from all corners of the world, the `AMR`
package is available in
<img src="lang_en.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
English,
<img src="lang_cs.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Czech,
<img src="lang_zh.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Chinese,
<img src="lang_da.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Danish,
<img src="lang_nl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Dutch,
<img src="lang_fi.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Finnish,
<img src="lang_fr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
French,
<img src="lang_de.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
German,
<img src="lang_el.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Greek,
<img src="lang_it.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Italian,
<img src="lang_ja.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Japanese,
<img src="lang_no.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Norwegian,
<img src="lang_pl.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Polish,
<img src="lang_pt.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Portuguese,
<img src="lang_ro.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Romanian,
<img src="lang_ru.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Russian,
<img src="lang_es.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Spanish,
<img src="lang_sv.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Swedish,
<img src="lang_tr.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Turkish, and
<img src="lang_uk.svg" style="height: 13px !important; border: 1px solid #cccccc; vertical-align: initial !important;">
Ukrainian. Antimicrobial drug (group) names and colloquial microorganism
names are provided in these languages.
### Practical examples
#### Filtering and selecting data
One of the most powerful functions of this package, aside from calculating and plotting AMR, is selecting and filtering based on antimicrobial columns. This can be done using the so-called [antimicrobial selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html), which work in base R, `dplyr` and `data.table`.
One of the most powerful functions of this package, aside from
calculating and plotting AMR, is selecting and filtering based on
antimicrobial columns. This can be done using the so-called
[antimicrobial
selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html),
which work in base R, `dplyr` and `data.table`.
```r
``` r
# AMR works great with dplyr, but it's not required or neccesary
library(AMR)
library(dplyr)
library(dplyr, warn.conflicts = FALSE)
example_isolates %>%
mutate(bacteria = mo_fullname()) %>%
@ -56,83 +152,106 @@ example_isolates %>%
select(bacteria,
aminoglycosides(),
carbapenems())
#> ℹ Using column 'mo' as input for mo_fullname()
#> ℹ Using column 'mo' as input for mo_is_gram_negative()
#> ℹ Using column 'mo' as input for mo_is_intrinsic_resistant()
#> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)
#> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)
#> # A tibble: 35 × 7
#> bacteria GEN TOB AMK KAN IPM MEM
#> <chr> <sir> <sir> <sir> <sir> <sir> <sir>
#> 1 Pseudomonas aeruginosa  I   S   NA  R   S   NA
#> 2 Pseudomonas aeruginosa  I   S   NA  R   S   NA
#> 3 Pseudomonas aeruginosa  I   S   NA  R   S   NA
#> 4 Pseudomonas aeruginosa  S   S   S   R   NA  S 
#> 5 Pseudomonas aeruginosa  S   S   S   R   S   S 
#> 6 Pseudomonas aeruginosa  S   S   S   R   S   S 
#> 7 Stenotrophomonas maltophilia  R   R   R   R   R   R 
#> 8 Pseudomonas aeruginosa  S   S   S   R   NA  S 
#> 9 Pseudomonas aeruginosa  S   S   S   R   NA  S 
#> 10 Pseudomonas aeruginosa  S   S   S   R   S   S 
#> # ℹ 25 more rows
```
With only having defined a row filter on Gram-negative bacteria with intrinsic resistance to cefotaxime (`mo_is_gram_negative()` and `mo_is_intrinsic_resistant()`) and a column selection on two antibiotic groups (`aminoglycosides()` and `carbapenems()`), the reference data about [all microorganisms](./reference/microorganisms.html) and [all antimicrobials](./reference/antimicrobials.html) in the `AMR` package make sure you get what you meant:
|bacteria | GEN | TOB | AMK | KAN | IPM | MEM |
|:------------------------------|:---:|:---:|:---:|:---:|:---:|:---:|
|*Pseudomonas aeruginosa* | I | S | | R | S | |
|*Pseudomonas aeruginosa* | I | S | | R | S | |
|*Pseudomonas aeruginosa* | I | S | | R | S | |
|*Pseudomonas aeruginosa* | S | S | S | R | | S |
|*Pseudomonas aeruginosa* | S | S | S | R | S | S |
|*Pseudomonas aeruginosa* | S | S | S | R | S | S |
|*Stenotrophomonas maltophilia* | R | R | R | R | R | R |
|*Pseudomonas aeruginosa* | S | S | S | R | | S |
|*Pseudomonas aeruginosa* | S | S | S | R | | S |
|*Pseudomonas aeruginosa* | S | S | S | R | S | S |
With only having defined a row filter on Gram-negative bacteria with
intrinsic resistance to cefotaxime (`mo_is_gram_negative()` and
`mo_is_intrinsic_resistant()`) and a column selection on two antibiotic
groups (`aminoglycosides()` and `carbapenems()`), the reference data
about [all microorganisms](./reference/microorganisms.html) and [all
antimicrobials](./reference/antimicrobials.html) in the `AMR` package
make sure you get what you meant.
#### Generating antibiograms
The `AMR` package supports generating traditional, combined, syndromic, and even weighted-incidence syndromic combination antibiograms (WISCA).
The `AMR` package supports generating traditional, combined, syndromic,
and even weighted-incidence syndromic combination antibiograms (WISCA).
If used inside [R Markdown](https://rmarkdown.rstudio.com) or [Quarto](https://quarto.org), the table will be printed in the right output format automatically (such as markdown, LaTeX, HTML, etc.).
If used inside [R Markdown](https://rmarkdown.rstudio.com) or
[Quarto](https://quarto.org), the table will be printed in the right
output format automatically (such as markdown, LaTeX, HTML, etc.).
```r
``` r
antibiogram(example_isolates,
antimicrobials = c(aminoglycosides(), carbapenems()),
formatting_type = 14)
antimicrobials = c(aminoglycosides(), carbapenems()))
#> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)
#> ℹ For carbapenems() using columns 'IPM' (imipenem) and 'MEM' (meropenem)
#> ℹ 502 combinations had less than minimum = 30 results and were ignored
```
| Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
|:-----------------|:--------------:|:--------------:|:--------------:|:----------:|:--------------:|:--------------:|
| CoNS | 0% (0-8%) | 86% (82-90%) | 52% (37-67%) | 0% (0-8%) | 52% (37-67%) | 22% (12-35%) |
| *E. coli* | 100% (98-100%) | 98% (96-99%) | 100% (99-100%) | | 100% (99-100%) | 97% (96-99%) |
| *E. faecalis* | 0% (0-9%) | 0% (0-9%) | 100% (91-100%) | 0% (0-9%) | | 0% (0-9%) |
| *K. pneumoniae* | | 90% (79-96%) | 100% (93-100%) | | 100% (93-100%) | 90% (79-96%) |
| *P. aeruginosa* | | 100% (88-100%) | | 0% (0-12%) | | 100% (88-100%) |
| *P. mirabilis* | | 94% (80-99%) | 94% (79-99%) | | | 94% (80-99%) |
| *S. aureus* | | 99% (97-100%) | | | | 98% (92-100%) |
| *S. epidermidis* | 0% (0-8%) | 79% (71-85%) | | 0% (0-8%) | | 51% (40-61%) |
| *S. hominis* | | 92% (84-97%) | | | | 85% (74-93%) |
| *S. pneumoniae* | 0% (0-3%) | 0% (0-3%) | | 0% (0-3%) | | 0% (0-3%) |
| Pathogen | Amikacin | Gentamicin | Imipenem | Kanamycin | Meropenem | Tobramycin |
|:---|:---|:---|:---|:---|:---|:---|
| CoNS | 0% (0-8%,N=43) | 86% (82-90%,N=309) | 52% (37-67%,N=48) | 0% (0-8%,N=43) | 52% (37-67%,N=48) | 22% (12-35%,N=55) |
| E. coli | 100% (98-100%,N=171) | 98% (96-99%,N=460) | 100% (99-100%,N=422) | | 100% (99-100%,N=418) | 97% (96-99%,N=462) |
| E. faecalis | 0% (0-9%,N=39) | 0% (0-9%,N=39) | 100% (91-100%,N=38) | 0% (0-9%,N=39) | | 0% (0-9%,N=39) |
| K. pneumoniae | | 90% (79-96%,N=58) | 100% (93-100%,N=51) | | 100% (93-100%,N=53) | 90% (79-96%,N=58) |
| P. aeruginosa | | 100% (88-100%,N=30) | | 0% (0-12%,N=30) | | 100% (88-100%,N=30) |
| P. mirabilis | | 94% (80-99%,N=34) | 94% (79-99%,N=32) | | | 94% (80-99%,N=34) |
| S. aureus | | 99% (97-100%,N=233) | | | | 98% (92-100%,N=86) |
| S. epidermidis | 0% (0-8%,N=44) | 79% (71-85%,N=163) | | 0% (0-8%,N=44) | | 51% (40-61%,N=89) |
| S. hominis | | 92% (84-97%,N=80) | | | | 85% (74-93%,N=62) |
| S. pneumoniae | 0% (0-3%,N=117) | 0% (0-3%,N=117) | | 0% (0-3%,N=117) | | 0% (0-3%,N=117) |
In combination antibiograms, it is clear that combined antimicrobials yield higher empiric coverage:
In combination antibiograms, it is clear that combined antimicrobials
yield higher empiric coverage:
```r
``` r
antibiogram(example_isolates,
antimicrobials = c("TZP", "TZP+TOB", "TZP+GEN"),
mo_transform = "gramstain",
formatting_type = 14)
mo_transform = "gramstain")
#> ℹ 3 combinations had less than minimum = 30 results and were ignored
```
|Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:-------------|:-----------------------:|:------------------------------------:|:------------------------------------:|
|Gram-negative | 88% (85-91%) | 99% (97-99%) | 98% (97-99%) |
|Gram-positive | 86% (82-89%) | 98% (96-98%) | 95% (93-97%) |
| Pathogen | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:---|:---|:---|:---|
| Gram-negative | 88% (85-91%,N=641) | 99% (97-99%,N=691) | 98% (97-99%,N=693) |
| Gram-positive | 86% (82-89%,N=345) | 98% (96-98%,N=1044) | 95% (93-97%,N=550) |
Like many other functions in this package, `antibiogram()` comes with support for 20 languages that are often detected automatically based on system language:
Like many other functions in this package, `antibiogram()` comes with
support for 20 languages that are often detected automatically based on
system language:
```r
``` r
antibiogram(example_isolates,
antimicrobials = c("cipro", "tobra", "genta"), # any arbitrary name or code will work
mo_transform = "gramstain",
ab_transform = "name",
formatting_type = 14,
language = "uk") # Ukrainian
#> ℹ 3 combinations had less than minimum = 30 results and were ignored
```
|Збудник | Гентаміцин | Тобраміцин | Ципрофлоксацин |
|:-------------|:------------:|:------------:|:--------------:|
|Грамнегативні | 96% (95-98%) | 96% (94-97%) | 91% (88-93%) |
|Грампозитивні | 63% (60-66%) | 34% (31-38%) | 77% (74-80%) |
| Збудник | Гентаміцин | Тобраміцин | Ципрофлоксацин |
|:--------------|:--------------------|:-------------------|:-------------------|
| Грамнегативні | 96% (95-98%,N=684) | 96% (94-97%,N=686) | 91% (88-93%,N=684) |
| Грампозитивні | 63% (60-66%,N=1170) | 34% (31-38%,N=665) | 77% (74-80%,N=724) |
#### Interpreting and plotting MIC and SIR values
The `AMR` package allows interpretation of MIC and disk diffusion values based on CLSI and EUCAST. Moreover, the `ggplot2` package is extended with new scale functions, to allow plotting of log2-distributed MIC values and SIR values.
The `AMR` package allows interpretation of MIC and disk diffusion values
based on CLSI and EUCAST. Moreover, the `ggplot2` package is extended
with new scale functions, to allow plotting of log2-distributed MIC
values and SIR values.
```r
``` r
library(ggplot2)
library(AMR)
@ -162,14 +281,15 @@ ggplot(data.frame(mic = some_mic_values,
```
<a href="./reference/plotting.html" title="Plotting Helpers for AMR Data Analysis">
<img src="./plot_readme.png" style="width: 1400px; max-width: 100%;">
<img src="./plot_readme.png" style="width: 1400px; max-width: 100%;">
</a>
#### Calculating resistance per group
For a manual approach, you can use the `resistance` or `susceptibility()` function:
For a manual approach, you can use the `resistance` or
`susceptibility()` function:
```r
``` r
example_isolates %>%
# group by ward:
group_by(ward) %>%
@ -178,17 +298,19 @@ example_isolates %>%
summarise(across(c(GEN, TOB),
list(total_R = resistance,
conf_int = function(x) sir_confidence_interval(x, collapse = "-"))))
#> # A tibble: 3 × 5
#> ward GEN_total_R GEN_conf_int TOB_total_R TOB_conf_int
#> <chr> <dbl> <chr> <dbl> <chr>
#> 1 Clinical 0.2289362 0.205-0.254 0.3147503 0.284-0.347
#> 2 ICU 0.2902655 0.253-0.33 0.4004739 0.353-0.449
#> 3 Outpatient 0.2 0.131-0.285 0.3676471 0.254-0.493
```
|ward | GEN_total_R | GEN_conf_int | TOB_total_R | TOB_conf_int |
|:----------|:-----------:|:------------:|:-----------:|:------------:|
|Clinical | 0.2289362 | 0.205-0.254 | 0.3147503 | 0.284-0.347 |
|ICU | 0.2902655 | 0.253-0.33 | 0.4004739 | 0.353-0.449 |
|Outpatient | 0.2000000 | 0.131-0.285 | 0.3676471 | 0.254-0.493 |
Or use [antimicrobial
selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html)
to select a series of antibiotic columns:
Or use [antimicrobial selectors](https://amr-for-r.org/reference/antimicrobial_selectors.html) to select a series of antibiotic columns:
```r
``` r
library(AMR)
library(dplyr)
@ -198,57 +320,86 @@ out <- example_isolates %>%
# calculate AMR using resistance(), over all aminoglycosides and polymyxins:
summarise(across(c(aminoglycosides(), polymyxins()),
resistance))
#> ℹ For aminoglycosides() using columns 'GEN' (gentamicin), 'TOB' (tobramycin), 'AMK' (amikacin), and 'KAN' (kanamycin)
#> ℹ For polymyxins() using column 'COL' (colistin)
#> Warning: There was 1 warning in `summarise()`.
#> ℹ In argument: `across(c(aminoglycosides(), polymyxins()), resistance)`.
#> ℹ In group 3: `ward = "Outpatient"`.
#> Caused by warning:
#> ! Introducing NA: only 23 results available for KAN in group: ward = "Outpatient" (minimum = 30).
out
#> # A tibble: 3 × 6
#> ward GEN TOB AMK KAN COL
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Clinical 0.2289362 0.3147503 0.6258993 1 0.7802956
#> 2 ICU 0.2902655 0.4004739 0.6624473 1 0.8574144
#> 3 Outpatient 0.2 0.3676471 0.6052632 NA 0.8888889
```
| ward | GEN | TOB | AMK | KAN | COL |
|:-----------|------:|------:|------:|------:|------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
```r
``` r
# transform the antibiotic columns to names:
out %>% set_ab_names()
#> # A tibble: 3 × 6
#> ward gentamicin tobramycin amikacin kanamycin colistin
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Clinical 0.2289362 0.3147503 0.6258993 1 0.7802956
#> 2 ICU 0.2902655 0.4004739 0.6624473 1 0.8574144
#> 3 Outpatient 0.2 0.3676471 0.6052632 NA 0.8888889
```
| ward | gentamicin | tobramycin | amikacin | kanamycin | colistin |
|:-----------|-----------:|-----------:|----------|----------:|----------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
```r
``` r
# transform the antibiotic column to ATC codes:
out %>% set_ab_names(property = "atc")
#> # A tibble: 3 × 6
#> ward J01GB03 J01GB01 J01GB06 J01GB04 J01XB01
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Clinical 0.2289362 0.3147503 0.6258993 1 0.7802956
#> 2 ICU 0.2902655 0.4004739 0.6624473 1 0.8574144
#> 3 Outpatient 0.2 0.3676471 0.6052632 NA 0.8888889
```
| ward | J01GB03 | J01GB01 | J01GB06 | J01GB04 | J01XB01 |
|:-----------|-----------:|-----------:|----------|----------:|----------:|
| Clinical | 0.229 | 0.315 | 0.626 | 1 | 0.780 |
| ICU | 0.290 | 0.400 | 0.662 | 1 | 0.857 |
| Outpatient | 0.200 | 0.368 | 0.605 | | 0.889 |
### What else can you do with this package?
This package was intended as a comprehensive toolbox for integrated AMR data analysis. This package can be used for:
This package was intended as a comprehensive toolbox for integrated AMR
data analysis. This package can be used for:
* Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the List of Prokaryotic names with Standing in Nomenclature ([LPSN]((https://lpsn.dsmz.de))) and the Global Biodiversity Information Facility ([GBIF](https://www.gbif.org)) ([manual](./reference/mo_property.html))
* Interpreting raw MIC and disk diffusion values, based on any CLSI or EUCAST guideline ([manual](./reference/as.sir.html))
* Retrieving antimicrobial drug names, doses and forms of administration from clinical health care records ([manual](./reference/ab_from_text.html))
* Determining first isolates to be used for AMR data analysis ([manual](./reference/first_isolate.html))
* Calculating antimicrobial resistance ([tutorial](./articles/AMR.html))
* Determining multi-drug resistance (MDR) / multi-drug resistant organisms (MDRO) ([tutorial](./articles/MDR.html))
* Calculating (empirical) susceptibility of both mono therapy and combination therapies ([tutorial](./articles/AMR.html))
* Apply AMR function in predictive modelling ([tutorial](./articles/AMR_with_tidymodels.html))
* Getting properties for any microorganism (like Gram stain, species, genus or family) ([manual](./reference/mo_property.html))
* Getting properties for any antimicrobial (like name, code of EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name) ([manual](./reference/ab_property.html))
* Plotting antimicrobial resistance ([tutorial](./articles/AMR.html))
* Applying EUCAST expert rules ([manual](./reference/eucast_rules.html))
* Getting SNOMED codes of a microorganism, or getting properties of a microorganism based on a SNOMED code ([manual](./reference/mo_property.html))
* Getting LOINC codes of an antibiotic, or getting properties of an antibiotic based on a LOINC code ([manual](./reference/ab_property.html))
* Machine reading the EUCAST and CLSI guidelines from 2011-2021 to translate MIC values and disk diffusion diameters to SIR ([link](./articles/datasets.html))
* Principal component analysis for AMR ([tutorial](./articles/PCA.html))
- Reference for the taxonomy of microorganisms, since the package
contains all microbial (sub)species from the List of Prokaryotic names
with Standing in Nomenclature ([LPSN]((https://lpsn.dsmz.de))) and the
Global Biodiversity Information Facility
([GBIF](https://www.gbif.org))
([manual](./reference/mo_property.html))
- Interpreting raw MIC and disk diffusion values, based on any CLSI or
EUCAST guideline ([manual](./reference/as.sir.html))
- Retrieving antimicrobial drug names, doses and forms of administration
from clinical health care records
([manual](./reference/ab_from_text.html))
- Determining first isolates to be used for AMR data analysis
([manual](./reference/first_isolate.html))
- Calculating antimicrobial resistance ([tutorial](./articles/AMR.html))
- Determining multi-drug resistance (MDR) / multi-drug resistant
organisms (MDRO) ([tutorial](./articles/MDR.html))
- Calculating (empirical) susceptibility of both mono therapy and
combination therapies ([tutorial](./articles/AMR.html))
- Apply AMR function in predictive modelling
([tutorial](./articles/AMR_with_tidymodels.html))
- Getting properties for any microorganism (like Gram stain, species,
genus or family) ([manual](./reference/mo_property.html))
- Getting properties for any antimicrobial (like name, code of
EARS-Net/ATC/LOINC/PubChem, defined daily dose or trade name)
([manual](./reference/ab_property.html))
- Plotting antimicrobial resistance ([tutorial](./articles/AMR.html))
- Applying EUCAST expert rules ([manual](./reference/eucast_rules.html))
- Getting SNOMED codes of a microorganism, or getting properties of a
microorganism based on a SNOMED code
([manual](./reference/mo_property.html))
- Getting LOINC codes of an antibiotic, or getting properties of an
antibiotic based on a LOINC code
([manual](./reference/ab_property.html))
- Machine reading the EUCAST and CLSI guidelines from 2011-2021 to
translate MIC values and disk diffusion diameters to SIR
([link](./articles/datasets.html))
- Principal component analysis for AMR ([tutorial](./articles/PCA.html))
### Get this package
@ -257,15 +408,21 @@ This package was intended as a comprehensive toolbox for integrated AMR data ana
[![CRAN](https://www.r-pkg.org/badges/version-ago/AMR)](https://cran.r-project.org/package=AMR)
[![CRANlogs](https://cranlogs.r-pkg.org/badges/grand-total/AMR)](https://cran.r-project.org/package=AMR)
This package is available [here on the official R network (CRAN)](https://cran.r-project.org/package=AMR). Install this package in R from CRAN by using the command:
This package is available [here on the official R network
(CRAN)](https://cran.r-project.org/package=AMR). Install this package in
R from CRAN by using the command:
```r
``` r
install.packages("AMR")
```
It will be downloaded and installed automatically. For RStudio, click on the menu *Tools* > *Install Packages...* and then type in "AMR" and press <kbd>Install</kbd>.
It will be downloaded and installed automatically. For RStudio, click on
the menu *Tools* \> *Install Packages…* and then type in “AMR” and press
<kbd>Install</kbd>.
**Note:** Not all functions on this website may be available in this latest release. To use all functions and data sets mentioned on this website, install the latest beta version.
**Note:** Not all functions on this website may be available in this
latest release. To use all functions and data sets mentioned on this
website, install the latest beta version.
#### Latest beta version
@ -274,11 +431,12 @@ It will be downloaded and installed automatically. For RStudio, click on the men
[![CodeFactor](https://www.codefactor.io/repository/github/msberends/amr/badge)](https://www.codefactor.io/repository/github/msberends/amr)
[![Codecov](https://codecov.io/gh/msberends/AMR/branch/main/graph/badge.svg)](https://codecov.io/gh/msberends/AMR?branch=main)
Please read our [Developer Guideline here](https://github.com/msberends/AMR/wiki/Developer-Guideline).
Please read our [Developer Guideline
here](https://github.com/msberends/AMR/wiki/Developer-Guideline).
To install the latest and unpublished beta version:
```r
``` r
install.packages("AMR", repos = "beta.amr-for-r.org")
# if this does not work, try to install directly from GitHub using the 'remotes' package:
@ -287,23 +445,30 @@ remotes::install_github("msberends/AMR")
### Get started
To find out how to conduct AMR data analysis, please [continue reading here to get started](./articles/AMR.html) or click a link in the ['How to' menu](./articles/).
To find out how to conduct AMR data analysis, please [continue reading
here to get started](./articles/AMR.html) or click a link in the [‘How
to’ menu](./articles/).
### Partners
The development of this package is part of, related to, or made possible by the following non-profit organisations and initiatives:
The initial development of this package was part of, related to, or made
possible by the following non-profit organisations and initiatives:
<div align="center">
<a href="https://www.rug.nl" title="University of Groningen"><img src="./logo_rug.svg" style="max-width: 200px;"></a>
<a href="https://www.umcg.nl" title="University Medical Center Groningen"><img src="./logo_umcg.svg" style="max-width: 200px;"></a>
<a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation"><img src="./logo_certe.svg" style="max-width: 200px;"></a>
<a href="https://www.deutschland-nederland.eu" title="EurHealth-1-Health"><img src="./logo_eh1h.png" style="max-width: 200px;"></a>
<a href="https://www.deutschland-nederland.eu" title="INTERREG"><img src="./logo_interreg.png" style="max-width: 200px;"></a>
<a href="https://www.rug.nl" title="University of Groningen"><img src="./logo_rug.svg" style="max-width: 200px;"></a>
<a href="https://www.umcg.nl" title="University Medical Center Groningen"><img src="./logo_umcg.svg" style="max-width: 200px;"></a>
<a href="https://www.certe.nl" title="Certe Medical Diagnostics and Advice Foundation"><img src="./logo_certe.svg" style="max-width: 200px;"></a>
<a href="https://www.deutschland-nederland.eu" title="EurHealth-1-Health"><img src="./logo_eh1h.png" style="max-width: 200px;"></a>
<a href="https://www.deutschland-nederland.eu" title="INTERREG"><img src="./logo_interreg.png" style="max-width: 200px;"></a>
</div>
### Copyright
This R package is free, open-source software and licensed under the [GNU General Public License v2.0 (GPL-2)](./LICENSE-text.html). In a nutshell, this means that this package:
This R package is free, open-source software and licensed under the [GNU
General Public License v2.0 (GPL-2)](./LICENSE-text.html). In a
nutshell, this means that this package:
- May be used for commercial purposes
@ -313,13 +478,16 @@ This R package is free, open-source software and licensed under the [GNU General
- May be modified, although:
- Modifications **must** be released under the same license when distributing the package
- Modifications **must** be released under the same license when
distributing the package
- Changes made to the code **must** be documented
- May be distributed, although:
- Source code **must** be made available when the package is distributed
- A copy of the license and copyright notice **must** be included with the package.
- Source code **must** be made available when the package is
distributed
- A copy of the license and copyright notice **must** be included with
the package.
- Comes with a LIMITATION of liability