8.3 KiB
AMR
This is an R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR).
This R package was created for academic research by PhD students of the Faculty of Medical Sciences of the University of Groningen (rug.nl) and the Medical Microbiology & Infection Prevention department of the University Medical Center Groningen (UMCG, umcg.nl). They also maintain this package, see Authors.
Why this package?
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).
With AMR you can also apply EUCAST rules to isolates, identify first isolates of every patient, translate antibiotic codes from the lab (like "AMOX"
) or the WHO (like "J01CA04"
) to trivial names (like "amoxicillin"
), or predict antimicrobial resistance for the nextcoming years with the rsi_predict
function.
For regular AMR analysis, the rsi
function can be used. This function als works with the dplyr
package (e.g. in conjunction with summarise
) to calculate the resistance percentages of different antibiotic columns of a table.
This package contains an example data set septic_patients
, consisting of 2000 isolates from anonymised septic patients between 2001 and 2017.
How to get it?
This package is available on CRAN and also here on GitHub.
From CRAN (recommended)
-
In RStudio (recommended):
- Click on
Tools
and thenInstall Packages...
- Type in
AMR
and press Install
- Click on
-
In R directly:
install.packages("AMR")
-
In Exploratory.io:
- (Exploratory.io costs $40/month but is free for students and teachers; if you have an
@umcg.nl
or@rug.nl
email address, click here to enroll) - Start the software and log in
- Click on your username at the right hand side top
- Click on
R Packages
- Click on the
Install
tab - Type in
AMR
and press Install - Once it’s installed it will show up in the
User Packages
section under thePackages
tab.
- (Exploratory.io costs $40/month but is free for students and teachers; if you have an
From GitHub (latest development version)
install.packages("devtools")
devtools::install_github("msberends/AMR")
How to use it?
# Call it with:
library(AMR)
# For a list of functions:
help(package = "AMR")
Overwrite/force resistance based on EUCAST rules
This is also called interpretive reading.
before <- data.frame(bactid = c("STAAUR", # Staphylococcus aureus
"ENCFAE", # Enterococcus faecalis
"ESCCOL", # Escherichia coli
"KLEPNE", # Klebsiella pneumoniae
"PSEAER"), # Pseudomonas aeruginosa
vanc = "-", # Vancomycin
amox = "-", # Amoxicillin
coli = "-", # Colistin
cfta = "-", # Ceftazidime
cfur = "-", # Cefuroxime
stringsAsFactors = FALSE)
before
# bactid vanc amox coli cfta cfur
# 1 STAAUR - - - - -
# 2 ENCFAE - - - - -
# 3 ESCCOL - - - - -
# 4 KLEPNE - - - - -
# 5 PSEAER - - - - -
# Now apply those rules; just need a column with bacteria ID's and antibiotic results:
after <- EUCAST_rules(before)
after
# bactid vanc amox coli cfta cfur
# 1 STAAUR - - R R -
# 2 ENCFAE - - R R R
# 3 ESCCOL R - - - -
# 4 KLEPNE R R - - -
# 5 PSEAER R R - - R
New classes
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
).
Both classes have extensions for existing generic functions like print
, summary
and plot
.
# Transform values to new classes
mic_data <- as.mic(c(">=32", "1.0", "8", "<=0.128", "8", "16", "16"))
rsi_data <- as.rsi(c(rep("S", 474), rep("I", 36), rep("R", 370)))
These functions also try to coerce valid values.
Quick overviews when just printing objects:
mic_data
# Class 'mic': 7 isolates
#
# <NA> 0
#
# <=0.128 1 8 16 >=32
# 1 1 2 2 1
rsi_data
# Class 'rsi': 880 isolates
#
# <NA>: 0
# Sum of S: 474
# Sum of IR: 406
# - Sum of R: 370
# - Sum of I: 36
#
# %S %IR %I %R
# 53.9 46.1 4.1 42.0
A plot of rsi_data
:
plot(rsi_data)
A plot of mic_data
(defaults to bar plot):
plot(mic_data)
Other epidemiological functions:
# Determine key antibiotic based on bacteria ID
key_antibiotics(...)
# Selection of first isolates of any patient
first_isolate(...)
# Calculate resistance levels of antibiotics, can be used with `summarise` (dplyr)
rsi(...)
# Predict resistance levels of antibiotics
rsi_predict(...)
# Get name of antibiotic by ATC code
abname(...)
abname("J01CR02", from = "atc", to = "umcg") # "AMCL"
Databases included in package
Datasets to work with antibiotics and bacteria properties.
# Dataset with ATC antibiotics codes, official names and DDD's (oral and parenteral)
ablist # A tibble: 420 x 12
# Dataset with bacteria codes and properties like gram stain and aerobic/anaerobic
bactlist # A tibble: 2,507 x 10
Authors
- Berends MS1,2, PhD Student
- Luz CF1, PhD Student
- Hassing EEA2, Data Analyst (contributor)
1 Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
2 Department of Medical, Market and Innovation (MMI), Certe Medische diagnostiek & advies, Groningen, the Netherlands
Copyright
This R package is licensed under the GNU General Public License (GPL) v2.0. In a nutshell, this means that this package:
-
May be used for commercial purposes
-
May be used for private purposes
-
May be modified, although:
- 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.
-
Comes with a LIMITATION of liability
-
Comes with NO warranty