AMR/reference/index.md

Package index

Introduction to the package

Please find the introduction to (and some general information about) our package here.

• AMR-package AMR :

  The AMR Package

Preparing data: microorganisms

These functions are meant to get taxonomically valid properties of microorganisms from any input, but also properties derived from taxonomy, such as the Gram stain (mo_gramstain()) , or mo_is_yeast(). Use mo_source() to teach this package how to translate your own codes to valid microorganisms, and use add_custom_microorganisms() to add your own custom microorganisms to this package.

• as.mo() is.mo() mo_uncertainties() mo_renamed() mo_failures() mo_reset_session() mo_cleaning_regex() : Transform Arbitrary Input to Valid Microbial Taxonomy
• 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_status() mo_pathogenicity() mo_gramstain() mo_is_gram_negative() mo_is_gram_positive() mo_is_yeast() mo_is_intrinsic_resistant() mo_oxygen_tolerance() mo_is_anaerobic() mo_snomed() mo_ref() mo_authors() mo_year() mo_lpsn() mo_mycobank() mo_gbif() mo_rank() mo_taxonomy() mo_synonyms() mo_current() mo_group_members() mo_info() mo_url() mo_property() : Get Properties of a Microorganism

• add_custom_microorganisms()

  clear_custom_microorganisms()

  Add Custom Microorganisms

• set_mo_source() get_mo_source() : User-Defined Reference Data Set for Microorganisms

Preparing data: antimicrobials

Use these functions to get valid properties of antimicrobials 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() ab_reset_session() : Transform Input to an Antibiotic ID
• ab_name() ab_cid() ab_synonyms() ab_tradenames() ab_group() ab_atc() ab_atc_group1() ab_atc_group2() ab_loinc() ab_ddd() ab_ddd_units() ab_info() ab_url() ab_property() set_ab_names() : 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()

  atc_online_ddd_units()

  Get ATC Properties from WHOCC Website

• add_custom_antimicrobials()

  clear_custom_antimicrobials()

  Add Custom Antimicrobials

Preparing data: antimicrobial results

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

• as.sir()

  NA_sir_

  is.sir()

  is_sir_eligible()

  sir_interpretation_history()

  Interpret MIC and Disk Diffusion as SIR, or Clean Existing SIR Data

• as.mic()

  is.mic()

  NA_mic_

  rescale_mic()

  mic_p50()

  mic_p90()

  droplevels(<mic>)

  Transform Input to Minimum Inhibitory Concentrations (MIC)

• as.disk() NA_disk_ is.disk() : Transform Input to Disk Diffusion Diameters
• eucast_rules() eucast_dosage() : Apply EUCAST Rules

• custom_eucast_rules()

  Define Custom EUCAST Rules

Analysing data

Use these function for the analysis part. You can use susceptibility() or resistance() on any antibiotic column. With antibiogram(), you can generate a traditional, combined, syndromic, or weighted-incidence syndromic combination antibiogram (WISCA). This function also comes with support for R Markdown and Quarto. 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 (carbapenems(), aminoglycosides()), or determine multi-drug resistant microorganisms (MDRO, mdro()).

• antibiogram()

  wisca()

  retrieve_wisca_parameters()

  plot(<antibiogram>)

  autoplot(<antibiogram>)

  knit_print(<antibiogram>)

  Generate Traditional, Combination, Syndromic, or WISCA Antibiograms

• resistance() susceptibility() sir_confidence_interval() proportion_R() proportion_IR() proportion_I() proportion_SI() proportion_S() proportion_df() sir_df() : Calculate Antimicrobial Resistance

• count_resistant() count_susceptible() count_S() count_SI() count_I() count_IR() count_R() count_all() n_sir() count_df() : Count Available Isolates

• get_episode() is_new_episode() : Determine Clinical or Epidemic Episodes

• first_isolate()

  filter_first_isolate()

  Determine First Isolates

• key_antimicrobials()

  all_antimicrobials()

  antimicrobials_equal()

  (Key) Antimicrobials for First Weighted Isolates

• mdro()

  brmo()

  mrgn()

  mdr_tb()

  mdr_cmi2012()

  eucast_exceptional_phenotypes()

  Determine Multidrug-Resistant Organisms (MDRO)

• custom_mdro_guideline()

  c(<custom_mdro_guideline>)

  Define Custom MDRO Guideline

• bug_drug_combinations()

  format(<bug_drug_combinations>)

  Determine Bug-Drug Combinations

• aminoglycosides()

  aminopenicillins()

  antifungals()

  antimycobacterials()

  betalactams()

  betalactams_with_inhibitor()

  carbapenems()

  cephalosporins()

  cephalosporins_1st()

  cephalosporins_2nd()

  cephalosporins_3rd()

  cephalosporins_4th()

  cephalosporins_5th()

  fluoroquinolones()

  glycopeptides()

  isoxazolylpenicillins()

  lincosamides()

  lipoglycopeptides()

  macrolides()

  monobactams()

  nitrofurans()

  oxazolidinones()

  penicillins()

  phenicols()

  polymyxins()

  quinolones()

  rifamycins()

  streptogramins()

  sulfonamides()

  tetracyclines()

  trimethoprims()

  ureidopenicillins()

  amr_class()

  amr_selector()

  administrable_per_os()

  administrable_iv()

  not_intrinsic_resistant()

  Antimicrobial Selectors

• top_n_microorganisms() :

  Filter Top n Microorganisms

• mean_amr_distance()

  amr_distance_from_row()

  Calculate the Mean AMR Distance

• resistance_predict()

  sir_predict()

  plot(<resistance_predict>)

  ggplot_sir_predict()

  autoplot(<resistance_predict>)

  Predict Antimicrobial Resistance

• guess_ab_col() : Guess Antibiotic Column

Plotting data

Use these functions for the plotting part. The scale_*_mic() functions extend the ggplot2 package to allow plotting of MIC values, even within a manually set range. If using plot() (base R) or autoplot() (ggplot2) on MIC values or disk diffusion values, the user can set the interpretation guideline to give the bars the right SIR colours. The ggplot_sir() function is a short wrapper for users not much accustomed to ggplot2 yet. The ggplot_pca() function is a specific function to plot so-called biplots for PCA (principal component analysis).

• scale_x_mic() scale_y_mic() scale_colour_mic() scale_fill_mic() scale_x_sir() scale_colour_sir() scale_fill_sir() plot(<mic>) autoplot(<mic>) plot(<disk>) autoplot(<disk>) plot(<sir>) autoplot(<sir>) facet_sir() scale_y_percent() scale_sir_colours() theme_sir() labels_sir_count() : Plotting Helpers for AMR Data Analysis

• ggplot_sir() geom_sir() :

  AMR Plots with ggplot2

• ggplot_pca() :

  PCA Biplot with ggplot2

AMR-specific options

The AMR package is customisable, by providing settings that can be set per user or per team. For example, the default interpretation guideline can be changed from EUCAST to CLSI, or a supported language can be set for the whole team (system-language independent) for antibiotic names in a foreign language.

• AMR-options : Options for the AMR package

Other: antiviral drugs

This package also provides extensive support for antiviral agents, even though it is not the primary scope of this package. Working with data containing information about antiviral drugs was never easier. Use these functions to get valid properties of antiviral drugs from any input or to clean your input. You can even retrieve drug names and doses from clinical text records, using av_from_text().

• as.av() is.av() : Transform Input to an Antiviral Drug ID
• av_name() av_cid() av_synonyms() av_tradenames() av_group() av_atc() av_loinc() av_ddd() av_ddd_units() av_info() av_url() av_property() : Get Properties of an Antiviral Drug
• av_from_text() : Retrieve Antiviral Drug Names and Doses from Clinical Text

Other: 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.

• microorganisms

  Data Set with 78 679 Taxonomic Records of Microorganisms

• antimicrobials antibiotics antivirals : Data Sets with 618 Antimicrobial Drugs

• clinical_breakpoints

  Data Set with Clinical Breakpoints for SIR Interpretation

• example_isolates

  Data Set with 2 000 Example Isolates

• microorganisms.codes

  Data Set with 6 036 Common Microorganism Codes

• microorganisms.groups

  Data Set with 534 Microorganisms In Species Groups

• intrinsic_resistant

  Data Set Denoting Bacterial Intrinsic Resistance

• dosage : Data Set with Treatment Dosages as Defined by EUCAST
• WHOCC : WHOCC: WHO Collaborating Centre for Drug Statistics Methodology

• example_isolates_unclean

  Data Set with Unclean Data

• WHONET : Data Set with 500 Isolates - WHONET Example

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

• export_ncbi_biosample()

  Export Data Set as NCBI BioSample Antibiogram

• availability() : Check Availability of Columns
• get_AMR_locale() set_AMR_locale() reset_AMR_locale() translate_AMR() : Translate Strings from the AMR Package

• italicise_taxonomy()

  italicize_taxonomy()

  Italicise Taxonomic Families, Genera, Species, Subspecies

• 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%` `%unlike%` `%like_case%` `%unlike_case%` : Vectorised 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_sir() : Random MIC Values/Disk Zones/SIR 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/arguments/datasets

These objects are deprecated, meaning that they will still work but show a warning that they will be removed in a future version.

• ab_class() ab_selector() : Deprecated Functions, Arguments, or Datasets