Background information on included data

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

microorganisms

Data set with 67,151 microorganisms

antibiotics antivirals

Data sets with 557 antimicrobials

intrinsic_resistant

Data set with bacterial intrinsic resistance

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

Data set with 5,583 common microorganism codes

microorganisms.old

Data set with previously accepted taxonomic names

WHONET

Data set with 500 isolates - WHONET example

Preparing data: microorganisms

These functions are meant to get taxonomically valid properties of microorganisms from any input. Use mo_source() to teach this package how to translate your own codes to valid microorganism codes.

as.mo() is.mo() mo_failures() mo_uncertainties() mo_renamed()

Transform input to a microorganism ID

mo_name() mo_fullname() mo_shortname() mo_subspecies() mo_species() mo_genus() mo_family() mo_order() mo_class() mo_phylum() mo_kingdom() mo_domain() mo_type() mo_gramstain() mo_is_gram_negative() mo_is_gram_positive() mo_is_intrinsic_resistant() mo_snomed() mo_ref() mo_authors() mo_year() mo_rank() mo_taxonomy() mo_synonyms() mo_info() mo_url() mo_property()

Get properties of a microorganism

set_mo_source() get_mo_source()

User-defined reference data set for microorganisms

Preparing data: antibiotics

Use these functions to get valid properties of antibiotics from any input or to clean your input. You can even retrieve drug names and doses from clinical text records, using ab_from_text().

as.ab() is.ab()

Transform input to an antibiotic ID

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_url() ab_property()

Get properties of an antibiotic

ab_from_text()

Retrieve antimicrobial drug names and doses from clinical text

atc_online_property() atc_online_groups() atc_online_ddd()

Get ATC properties from WHOCC website

Preparing data: antimicrobial resistance

With as.mic() and as.disk() you can transform your raw input to valid MIC or disk diffusion values. Use as.rsi() for cleaning raw data to let it only contain “R”, “I” and “S”, or to interpret MIC or disk diffusion values as R/SI based on the lastest EUCAST and CLSI guidelines. Afterwards, you can extend antibiotic interpretations by applying EUCAST rules with eucast_rules().

as.rsi() is.rsi() is.rsi.eligible()

Interpret MIC and disk values, or clean raw R/SI data

as.mic() is.mic()

Transform input to minimum inhibitory concentrations (MIC)

as.disk() is.disk()

Transform input to disk diffusion diameters

eucast_rules()

Apply EUCAST rules

plot(<disk>) plot(<mic>) barplot(<mic>) plot(<rsi>) barplot(<rsi>)

Plotting for classes rsi, mic and disk

Analysing data: antimicrobial resistance

Use these function for the analysis part. You can use susceptibility() or resistance() on any antibiotic column. Be sure to first select the isolates that are appropiate for analysis, by using first_isolate() or is_new_episode(). You can also filter your data on certain resistance in certain antibiotic classes (filter_ab_class()), or determine multi-drug resistant microorganisms (MDRO, mdro()).

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

get_episode() is_new_episode()

Determine (new) episodes for patients

first_isolate() filter_first_isolate() filter_first_weighted_isolate()

Determine first (weighted) isolates

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)

ggplot_rsi() geom_rsi() facet_rsi() scale_y_percent() scale_rsi_colours() theme_rsi() labels_rsi_count()

AMR plots with ggplot2

bug_drug_combinations() format(<bug_drug_combinations>)

Determine bug-drug combinations

ab_class() aminoglycosides() carbapenems() cephalosporins() cephalosporins_1st() cephalosporins_2nd() cephalosporins_3rd() cephalosporins_4th() cephalosporins_5th() fluoroquinolones() glycopeptides() macrolides() penicillins() tetracyclines()

Antibiotic class selectors

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_penicillins() filter_tetracyclines()

Filter isolates on result in antimicrobial class

resistance_predict() rsi_predict() plot(<resistance_predict>) ggplot_rsi_predict()

Predict antimicrobial resistance

guess_ab_col()

Guess antibiotic column

Other: miscellaneous 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) {...}.

age_groups()

Split ages into age groups

age()

Age in years of individuals

availability()

Check availability of columns

get_locale()

Translate strings from AMR package

ggplot_pca()

PCA biplot with ggplot2

inner_join_microorganisms() left_join_microorganisms() right_join_microorganisms() full_join_microorganisms() semi_join_microorganisms() anti_join_microorganisms()

Join microorganisms to a data set

like() `%like%` `%like_case%`

Pattern matching with keyboard shortcut

mo_matching_score()

Calculate the matching score for microorganisms

pca()

Principal Component Analysis (for AMR)

random_mic() random_disk() random_rsi()

Random MIC values/disk zones/RSI generation

Other: statistical tests

Some statistical tests or methods are not part of base R and were added to this package for convenience.

g.test()

G-test for Count Data

kurtosis()

Kurtosis of the sample

skewness()

Skewness of the sample

Other: 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.

p_symbol()

Deprecated functions