Function reference • AMR (for R)

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
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()` `clear_mo_history()`	Transform to microorganism ID
`as.rsi()` `is.rsi()` `is.rsi.eligible()`	Class 'rsi'
`set_mo_source()` `get_mo_source()`	Use predefined reference data set
`eucast_rules()`	EUCAST rules
`rsi_translation`	Data set for RSI interpretation
`guess_ab_col()`	Guess antibiotic column
`read.4D()`	Read data from 4D database
Adding variables to your data Functions to add new data to existing data, like 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.
`first_isolate()` `filter_first_isolate()` `filter_first_weighted_isolate()`	Determine first (weighted) isolates
`mdro()` `brmo()` `mrgn()` `mdr_tb()` `eucast_exceptional_phenotypes()`	Determine multidrug-resistant organisms (MDRO)
`key_antibiotics()` `key_antibiotics_equal()`	Key antibiotics for first weighted isolates
`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_ref()` `mo_authors()` `mo_year()` `mo_rank()` `mo_taxonomy()` `mo_synonyms()` `mo_info()` `mo_url()` `mo_property()`	Property of a microorganism
`ab_name()` `ab_atc()` `ab_cid()` `ab_synonyms()` `ab_tradenames()` `ab_group()` `ab_atc_group1()` `ab_atc_group2()` `ab_ddd()` `ab_info()` `ab_property()`	Property of an antibiotic
`age()`	Age in years of individuals
`age_groups()`	Split ages into age groups
`p_symbol()`	Symbol of a p value
`inner_join_microorganisms()` `left_join_microorganisms()` `right_join_microorganisms()` `full_join_microorganisms()` `semi_join_microorganisms()` `anti_join_microorganisms()`	Join a table with `microorganisms`
`atc_online_property()` `atc_online_groups()` `atc_online_ddd()`	Get ATC properties from WHOCC website
Analysing your data Functions for conducting AMR analysis, like counting isolates, calculating resistance or susceptibility, or make plots.
`availability()`	Check availability of columns
`bug_drug_combinations()` `format(<bug_drug_combinations>)`	Determine bug-drug combinations
`count_R()` `count_IR()` `count_I()` `count_SI()` `count_S()` `count_all()` `n_rsi()` `count_df()`	Count isolates
`portion_R()` `portion_IR()` `portion_I()` `portion_SI()` `portion_S()` `portion_df()` `rsi_df()`	Calculate resistance of isolates
`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 antibiotic 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`
`kurtosis()`	Kurtosis of the sample
`resistance_predict()` `rsi_predict()` `plot(<resistance_predict>)` `ggplot_rsi_predict()`	Predict antimicrobial resistance
`skewness()`	Skewness of the sample
Included data sets References for microorganisms and antibiotics, and even a genuine data set with isolates from septic patients.
`antibiotics`	Data set with ~450 antibiotics
`microorganisms`	Data set with ~70,000 microorganisms
`example_isolates`	Data set with 2,000 blood culture isolates
`WHONET`	Data set with 500 isolates - WHONET example
`microorganisms.codes`	Translation table for common microorganism codes
`microorganisms.old`	Data set with previously accepted taxonomic names
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
Extended functions These functions are extensions of functions in other packages.
`scale_type.mo()` `scale_type.ab()`	Extended functions
functions These functions are deprecated, meaning that they still work but show a warning with every use and will be removed in a future version.
`as.atc()` `p.symbol()`	Deprecated functions

Reference

Background information

Cleaning your data

Adding variables to your data

Analysing your data

Included data sets

Other functions

Extended functions

functions

Contents