Function reference • AMR (for R)

Cleaning your data Functions for cleaning and optimising your data, to be able to add variables later on (like taxonomic properties) or to fix and extend antibiotic interpretations by applying EUCAST rules.
`as.ab()` `is.ab()`	Transform to antibiotic ID
`as.disk()` `is.disk()`	Class 'disk'
`as.mic()` `is.mic()`	Class 'mic'
`as.mo()` `is.mo()` `mo_failures()` `mo_uncertainties()` `mo_renamed()`	Transform to microorganism ID
`as.rsi()` `is.rsi()` `is.rsi.eligible()`	Class 'rsi'
`eucast_rules()`	Apply EUCAST rules
`guess_ab_col()`	Guess antibiotic column
`set_mo_source()` `get_mo_source()`	Use predefined reference data set
`read.4D()`	Read data from 4D database
Enhancing your data Functions to add new data to your existing data, such as the determination of first isolates, multi-drug resistant microorganisms (MDRO), getting properties of microorganisms or antibiotics and determining the age of patients or divide ages into age groups.
`ab_name()` `ab_atc()` `ab_cid()` `ab_synonyms()` `ab_tradenames()` `ab_group()` `ab_atc_group1()` `ab_atc_group2()` `ab_loinc()` `ab_ddd()` `ab_info()` `ab_property()`	Property of an antibiotic
`age_groups()`	Split ages into age groups
`age()`	Age in years of individuals
`atc_online_property()` `atc_online_groups()` `atc_online_ddd()`	Get ATC properties from WHOCC website
`first_isolate()` `filter_first_isolate()` `filter_first_weighted_isolate()`	Determine first (weighted) isolates
`inner_join_microorganisms()` `left_join_microorganisms()` `right_join_microorganisms()` `full_join_microorganisms()` `semi_join_microorganisms()` `anti_join_microorganisms()`	Join microorganisms to a data set
`key_antibiotics()` `key_antibiotics_equal()`	Key antibiotics for first weighted isolates
`mdro()` `brmo()` `mrgn()` `mdr_tb()` `mdr_cmi2012()` `eucast_exceptional_phenotypes()`	Determine multidrug-resistant organisms (MDRO)
`mo_name()` `mo_fullname()` `mo_shortname()` `mo_subspecies()` `mo_species()` `mo_genus()` `mo_family()` `mo_order()` `mo_class()` `mo_phylum()` `mo_kingdom()` `mo_type()` `mo_gramstain()` `mo_snomed()` `mo_ref()` `mo_authors()` `mo_year()` `mo_rank()` `mo_taxonomy()` `mo_synonyms()` `mo_info()` `mo_url()` `mo_property()`	Property of a microorganism
`p_symbol()`	Symbol of a p-value
Analysing your data Functions for conducting AMR analysis, like counting isolates, calculating resistance or susceptibility, or make plots.
`resistance()` `susceptibility()` `proportion_R()` `proportion_IR()` `proportion_I()` `proportion_SI()` `proportion_S()` `proportion_df()` `rsi_df()`	Calculate microbial resistance
`count_resistant()` `count_susceptible()` `count_R()` `count_IR()` `count_I()` `count_SI()` `count_S()` `count_all()` `n_rsi()` `count_df()`	Count available isolates
`availability()`	Check availability of columns
`bug_drug_combinations()` `format(<bug_drug_combinations>)`	Determine bug-drug combinations
`resistance_predict()` `rsi_predict()` `plot(<resistance_predict>)` `ggplot_rsi_predict()`	Predict antimicrobial resistance
`pca()`	Principal Component Analysis (for AMR)
`filter_ab_class()` `filter_aminoglycosides()` `filter_carbapenems()` `filter_cephalosporins()` `filter_1st_cephalosporins()` `filter_2nd_cephalosporins()` `filter_3rd_cephalosporins()` `filter_4th_cephalosporins()` `filter_5th_cephalosporins()` `filter_fluoroquinolones()` `filter_glycopeptides()` `filter_macrolides()` `filter_tetracyclines()`	Filter isolates on result in antimicrobial class
`g.test()`	G-test for Count Data
`ggplot_rsi()` `geom_rsi()` `facet_rsi()` `scale_y_percent()` `scale_rsi_colours()` `theme_rsi()` `labels_rsi_count()`	AMR plots with `ggplot2`
`ggplot_pca()`	PCA biplot with `ggplot2`
`kurtosis()`	Kurtosis of the sample
`skewness()`	Skewness of the sample
Included data sets Scientifically reliable references for microorganisms and antibiotics, and example data sets to use for practise.
`microorganisms`	Data set with 69,447 microorganisms
`antibiotics` `antivirals`	Data sets with 557 antimicrobials
`example_isolates`	Data set with 2,000 example isolates
`example_isolates_unclean`	Data set with unclean data
`rsi_translation`	Data set for R/SI interpretation
`microorganisms.codes`	Translation table for common microorganism codes
`microorganisms.old`	Data set with previously accepted taxonomic names
`WHONET`	Data set with 500 isolates - WHONET example
Background information Some pages about our package and its external sources. Be sure to read our How To’s for more information about how to work with functions in this package.
`AMR`	The `AMR` Package
`catalogue_of_life`	The Catalogue of Life
`catalogue_of_life_version()`	Version info of included Catalogue of Life
`WHOCC`	WHOCC: WHO Collaborating Centre for Drug Statistics Methodology
`lifecycle`	Lifecycles of functions in the `AMR` package
Other functions These functions are mostly for internal use, but some of them may also be suitable for your analysis. Especially the ‘like’ function can be useful: `if (x %like% y) {...}`.
`get_locale()`	Translate strings from AMR package
`like()` `%like%` `%like_case%`	Pattern Matching
`reexports`	Objects exported from other packages
`scale_type.mo()` `scale_type.ab()` `vec_ptype2.mo()` `vec_cast.mo()` `vec_ptype2.ab()` `vec_cast.ab()`	Methods for tidyverse
Deprecated functions These functions are deprecated, meaning that they will still work but show a warning with every use and will be removed in a future version.
`portion_R()` `portion_IR()` `portion_I()` `portion_SI()` `portion_S()` `portion_df()`	Deprecated functions

Reference

Cleaning your data

Enhancing your data

Analysing your data

Included data sets

Background information

Other functions

Deprecated functions