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()` `clear_mo_history()`	Transform to microorganism ID
`as.rsi()` `is.rsi()` `is.rsi.eligible()`	Class 'rsi'
`eucast_rules()`	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
`rsi_translation`	Data set for RSI interpretation
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_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 a table with `microorganisms`
`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_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.
`availability()`	Check availability of columns
`bug_drug_combinations()` `format(<bug_drug_combinations>)`	Determine bug-drug combinations
`count_resistant()` `count_susceptible()` `count_R()` `count_IR()` `count_I()` `count_SI()` `count_S()` `count_all()` `n_rsi()` `count_df()`	Count 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()` `susceptibility()` `proportion_R()` `proportion_IR()` `proportion_I()` `proportion_SI()` `proportion_S()` `proportion_df()` `rsi_df()`	Calculate microbial resistance
`resistance_predict()` `rsi_predict()` `plot(<resistance_predict>)` `ggplot_rsi_predict()`	Predict antimicrobial resistance
`skewness()`	Skewness of the sample
Included data sets Scientifically reliable references for microorganisms and antibiotics, and example data sets to use for practise.
`antibiotics`	Data set with ~450 antibiotics
`antivirals`	Data set with ~100 antivirals
`example_isolates`	Data set with 2,000 example isolates
`microorganisms.codes`	Translation table for common microorganism codes
`microorganisms.old`	Data set with previously accepted taxonomic names
`microorganisms`	Data set with ~70,000 microorganisms
`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
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
`reexports`	Objects exported from other packages
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.
`p.symbol()` `portion_R()` `portion_IR()` `portion_I()` `portion_SI()` `portion_S()`	Deprecated functions

Reference

Cleaning your data

Enhancing your data

Analysing your data

Included data sets

Background information

Other functions

Extended functions

functions

Contents