1
0
mirror of https://github.com/msberends/AMR.git synced 2024-12-25 20:06:12 +01:00
AMR/README.md

6.2 KiB

AMR

This is an R package to simplify the analysis and prediction of Antimicrobial Resistance (AMR).

logo_unilogo_umcg

This R package was created for academic research by PhD students of the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology & Infection Prevention department of the University Medical Center Groningen (UMCG). 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 S3 classes to work with MIC values and antimicrobial interpretations (i.e. values S, I and R).

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.

It also contains functions to translate antibiotic codes from the lab (like "AMOX") or the WHO (like "J01CA04") to trivial names (like "amoxicillin") and vice versa.

How to get it?

CRAN_Badge

This package is available on CRAN (latest stable version) and also here on GitHub (latest development version).

For RStudio:

  • Click on Tools and then Install Packages...
  • Type in AMR and press Install

Or in the R console:

install.packages("AMR")

Latest development version from GitHub

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)

example

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

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

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