Fixed floating point error for some MIC compa in EUCAST 2020 guideline
Interpretation from MIC values to R/SI can now be used with mutate_at() of the dplyr package:
Added antibiotic abbreviations for a laboratory manufacturer (GLIMS) for cefuroxime, cefotaxime, ceftazidime, cefepime, cefoxitin and trimethoprim/sulfamethoxazole
Added uti (as abbreviation of urinary tract infections) as parameter to as.rsi(), so interpretation of MIC values and disk zones can be made dependent on isolates specifically from UTIs
This software is now out of beta and considered stable. Nonetheless, this package will be developed continually.
as.rsi() and inferred resistance and susceptibility using eucast_rules().Support for LOINC codes in the antibiotics data set. Use ab_loinc() to retrieve LOINC codes, or use a LOINC code for input in any ab_* function:
Support for SNOMED CT codes in the microorganisms data set. Use mo_snomed() to retrieve SNOMED codes, or use a SNOMED code for input in any mo_* function:
mo_snomed("S. aureus")
#> [1] 115329001 3092008 113961008
mo_name(115329001)
#> [1] "Staphylococcus aureus"
mo_gramstain(115329001)
#> [1] "Gram-positive"as.mo() function previously wrote to the package folder to improve calculation speed for previously calculated results. This is no longer the case, to comply with CRAN policies. Consequently, the function clear_mo_history() was removed.as.rsi()
as.mo() (and consequently all mo_* functions, that use as.mo() internally):
as.mo("Methicillin-resistant S.aureus")
as.disk() limited to a maximum of 50 millimeterstidyverse
as.ab(): support for drugs starting with “co-” like co-amoxiclav, co-trimoxazole, co-trimazine and co-trimazole (thanks to Peter Dutey)antibiotics data set (thanks to Peter Dutey):
RIF) to rifampicin/isoniazid (RFI). Please note that the combination rifampicin/isoniazid has no DDDs defined, so e.g. ab_ddd("Rimactazid") will now return NA.SMX) to trimethoprim/sulfamethoxazole (SXT)microorganisms data set, which means that the new order Enterobacterales now consists of a part of the existing family Enterobacteriaceae, but that this family has been split into other families as well (like Morganellaceae and Yersiniaceae). Although published in 2016, this information is not yet in the Catalogue of Life version of 2019. All MDRO determinations with mdro() will now use the Enterobacterales order for all guidelines before 2016 that were dependent on the Enterobacteriaceae family.
Functions susceptibility() and resistance() as aliases of proportion_SI() and proportion_R(), respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.
library(dplyr)
example_isolates %>%
group_by(bug = mo_name(mo)) %>%
summarise(amoxicillin = resistance(AMX),
amox_clav = resistance(AMC)) %>%
filter(!is.na(amoxicillin) | !is.na(amox_clav))Support for a new MDRO guideline: Magiorakos AP, Srinivasan A et al. “Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.” Clinical Microbiology and Infection (2012).
mdro() functionmdro(...., verbose = TRUE)) returns an informative data set where the reason for MDRO determination is given for every isolate, and an list of the resistant antimicrobial agentsData set antivirals, containing all entries from the ATC J05 group with their DDDs for oral and parenteral treatment
as.mo():
Now allows “ou” where “au” should have been used and vice versa
More intelligent way of coping with some consonants like “l” and “r”
Added a score (a certainty percentage) to mo_uncertainties(), that is calculated using the Levenshtein distance:
as.mo(c("Stafylococcus aureus",
"staphylokok aureuz"))
#> Warning:
#> Results of two values were guessed with uncertainty. Use mo_uncertainties() to review them.
#> Class 'mo'
#> [1] B_STPHY_AURS B_STPHY_AURS
mo_uncertainties()
#> "Stafylococcus aureus" -> Staphylococcus aureus (B_STPHY_AURS, score: 95.2%)
#> "staphylokok aureuz" -> Staphylococcus aureus (B_STPHY_AURS, score: 85.7%)as.atc() - this function was replaced by ab_atc()
portion_* functions to proportion_*. All portion_* functions are still available as deprecated functions, and will return a warning when used.as.rsi() over a data set, it will now print the guideline that will be used if it is not specified by the usereucast_rules():
eucast_rules() are now applied first and not as last anymore. This is to improve the dependency on certain antibiotics for the official EUCAST rules. Please see ?eucast_rules.as.rsi() where the input is NA
mdro() and eucast_rules()
antibiotics data setexample_isolates data set to better reflect realitymo_info()
clean to cleaner, as this package was renamed accordingly upon CRAN requestDetermination of first isolates now excludes all ‘unknown’ microorganisms at default, i.e. microbial code "UNKNOWN". They can be included with the new parameter include_unknown:
first_isolate(..., include_unknown = TRUE)For WHONET users, this means that all records/isolates with organism code "con" (contamination) will be excluded at default, since as.mo("con") = "UNKNOWN". The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.
For code consistency, classes ab and mo will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in NA:
# how it works in base R:
x <- factor("A")
x[1] <- "B"
#> Warning message:
#> invalid factor level, NA generated
# how it now works similarly for classes 'mo' and 'ab':
x <- as.mo("E. coli")
x[1] <- "testvalue"
#> Warning message:
#> invalid microorganism code, NA generatedThis is important, because a value like "testvalue" could never be understood by e.g. mo_name(), although the class would suggest a valid microbial code.
Function freq() has moved to a new package, clean (CRAN link), since creating frequency tables actually does not fit the scope of this package. The freq() function still works, since it is re-exported from the clean package (which will be installed automatically upon updating this AMR package).
Renamed data set septic_patients to example_isolates
Function bug_drug_combinations() to quickly get a data.frame with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with mo_shortname() at default:
x <- bug_drug_combinations(example_isolates)
#> NOTE: Using column `mo` as input for `col_mo`.
x[1:4, ]
#> mo ab S I R total
#> 1 A. baumannii AMC 0 0 3 3
#> 2 A. baumannii AMK 0 0 0 0
#> 3 A. baumannii AMP 0 0 3 3
#> 4 A. baumannii AMX 0 0 3 3
#> NOTE: Use 'format()' on this result to get a publicable/printable format.
# change the transformation with the FUN argument to anything you like:
x <- bug_drug_combinations(example_isolates, FUN = mo_gramstain)
#> NOTE: Using column `mo` as input for `col_mo`.
x[1:4, ]
#> mo ab S I R total
#> 1 Gram-negative AMC 469 89 174 732
#> 2 Gram-negative AMK 251 0 2 253
#> 3 Gram-negative AMP 227 0 405 632
#> 4 Gram-negative AMX 227 0 405 632
#> NOTE: Use 'format()' on this result to get a publicable/printable format.You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R format() function:
format(x, combine_IR = FALSE)Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for portion_* functions or count_* functions. This can be used to determine the empiric susceptibility of a combination therapy. A new parameter only_all_tested (which defaults to FALSE) replaces the old also_single_tested and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the portion and count help pages), where the %SI is being determined:
# --------------------------------------------------------------------
# only_all_tested = FALSE only_all_tested = TRUE
# ----------------------- -----------------------
# Drug A Drug B include as include as include as include as
# numerator denominator numerator denominator
# -------- -------- ---------- ----------- ---------- -----------
# S or I S or I X X X X
# R S or I X X X X
# <NA> S or I X X - -
# S or I R X X X X
# R R - X - X
# <NA> R - - - -
# S or I <NA> X X - -
# R <NA> - - - -
# <NA> <NA> - - - -
# --------------------------------------------------------------------Since this is a major change, usage of the old also_single_tested will throw an informative error that it has been replaced by only_all_tested.
tibble printing support for classes rsi, mic, disk, ab mo. When using tibbles containing antimicrobial columns, values S will print in green, values I will print in yellow and values R will print in red. Microbial IDs (class mo) will emphasise on the genus and species, not on the kingdom.
as.mo() (of which some led to additions to the microorganisms data set). Many thanks to all contributors that helped improving the algorithms.
B_ENTRC_FAE could have been both E. faecalis and E. faecium. Its new code is B_ENTRC_FCLS and E. faecium has become B_ENTRC_FACM. Also, the Latin character æ (ae) is now preserved at the start of each genus and species abbreviation. For example, the old code for Aerococcus urinae was B_ARCCC_NAE. This is now B_AERCC_URIN. IMPORTANT: Old microorganism IDs are still supported, but support will be dropped in a future version. Use as.mo() on your old codes to transform them to the new format. Using functions from the mo_* family (like mo_name() and mo_gramstain()) on old codes, will throw a warning.as.ab(), including bidirectional language supportmdro() function, to determine multi-drug resistant organismseucast_rules():
eucast_rules(..., verbose = TRUE)) returns more informative and readable outputAMR:::get_column_abx())atc - using as.atc() is now deprecated in favour of ab_atc() and this will return a character, not the atc class anymoreabname(), ab_official(), atc_name(), atc_official(), atc_property(), atc_tradenames(), atc_trivial_nl()
mo_shortname()
mo_* functions where the coercion uncertainties and failures would not be available through mo_uncertainties() and mo_failures() anymorecountry parameter of mdro() in favour of the already existing guideline parameter to support multiple guidelines within one countryname of RIF is now Rifampicin instead of Rifampinantibiotics data set is now sorted by name and all cephalosporins now have their generation between bracketsguess_ab_col() which is now 30 times faster for antibiotic abbreviationsfilter_ab_class() to be more reliable and to support 5th generation cephalosporinsavailability() now uses portion_R() instead of portion_IR(), to comply with EUCAST insightsage() and age_groups() now have a na.rm parameter to remove empty valuesp.symbol() to p_symbol() (the former is now deprecated and will be removed in a future version)x in age_groups() will now introduce NAs and not return an error anymorekey_antibiotics() on foreign systemsmdr_tb()
as.mic())Function rsi_df() to transform a data.frame to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions count_df() and portion_df() to immediately show resistance percentages and number of available isolates:
Support for all scientifically published pathotypes of E. coli to date (that we could find). Supported are:
All these lead to the microbial ID of E. coli:
as.mo("UPEC")
# B_ESCHR_COL
mo_name("UPEC")
# "Escherichia coli"
mo_gramstain("EHEC")
# "Gram-negative"Function mo_info() as an analogy to ab_info(). The mo_info() prints a list with the full taxonomy, authors, and the URL to the online database of a microorganism
Function mo_synonyms() to get all previously accepted taxonomic names of a microorganism
count_df() and portion_df() are now lowercaseas.ab() and as.mo() to understand even more severely misspelled inputas.ab() now allows spaces for coercing antibiotics namesggplot2 methods for automatically determining the scale type of classes mo and ab
"bacteria" from getting coerced by as.ab() because Bacterial is a brand name of trimethoprim (TMP)eucast_rules() and mdro()
latest_annual_release from the catalogue_of_life_version() functionPVM1 from the antibiotics data set as this was a duplicate of PME
as.mo()
plot() and barplot() for MIC and RSI classesas.mo()
as.rsi() on an MIC value (created with as.mic()), a disk diffusion value (created with the new as.disk()) or on a complete date set containing columns with MIC or disk diffusion values.mo_name() as alias of mo_fullname()
mdr_tb()) and added a new vignette about MDR. Read this tutorial here on our website.Fixed a critical bug in first_isolate() where missing species would lead to incorrect FALSEs. This bug was not present in AMR v0.5.0, but was in v0.6.0 and v0.6.1.
Fixed a bug in eucast_rules() where antibiotics from WHONET software would not be recognised
Completely reworked the antibiotics data set:
All entries now have 3 different identifiers:
ab contains a human readable EARS-Net code, used by ECDC and WHO/WHONET - this is the primary identifier used in this packageatc contains the ATC code, used by WHO/WHOCCcid contains the CID code (Compound ID), used by PubChemBased on the Compound ID, almost 5,000 official brand names have been added from many different countries
All references to antibiotics in our package now use EARS-Net codes, like AMX for amoxicillin
Functions atc_certe, ab_umcg and atc_trivial_nl have been removed
All atc_* functions are superceded by ab_* functions
All output will be translated by using an included translation file which can be viewed here.
Please create an issue in one of our repositories if you want additions in this file.
Improvements to plotting AMR results with ggplot_rsi():
colours to set the bar colourstitle, subtitle, caption, x.title and y.title to set titles and axis descriptionsImproved intelligence of looking up antibiotic columns in a data set using guess_ab_col()
Added ~5,000 more old taxonomic names to the microorganisms.old data set, which leads to better results finding when using the as.mo() function
This package now honours the new EUCAST insight (2019) that S and I are but classified as susceptible, where I is defined as ‘increased exposure’ and not ‘intermediate’ anymore. For functions like portion_df() and count_df() this means that their new parameter combine_SI is TRUE at default. Our plotting function ggplot_rsi() also reflects this change since it uses count_df() internally.
The age() function gained a new parameter exact to determine ages with decimals
Removed deprecated functions guess_mo(), guess_atc(), EUCAST_rules(), interpretive_reading(), rsi()
Frequency tables (freq()):
speed improvement for microbial IDs
fixed factor level names for R Markdown
when all values are unique it now shows a message instead of a warning
support for boxplots:
Removed all hardcoded EUCAST rules and replaced them with a new reference file which can be viewed here.
Please create an issue in one of our repositories if you want changes in this file.
Added ceftazidim intrinsic resistance to Streptococci
Changed default settings for age_groups(), to let groups of fives and tens end with 100+ instead of 120+
Fix for freq() for when all values are NA
Fix for first_isolate() for when dates are missing
Improved speed of guess_ab_col()
Function as.mo() now gently interprets any number of whitespace characters (like tabs) as one space
Function as.mo() now returns UNKNOWN for "con" (WHONET ID of ‘contamination’) and returns NA for "xxx"(WHONET ID of ‘no growth’)
Small algorithm fix for as.mo()
Removed viruses from data set microorganisms.codes and cleaned it up
Fix for mo_shortname() where species would not be determined correctly
eucast_rules() with verbose = TRUE
New website!
We’ve got a new website: https://msberends.gitlab.io/AMR (built with the great pkgdown)
BREAKING: removed deprecated functions, parameters and references to ‘bactid’. Use as.mo() to identify an MO code.
Catalogue of Life as a new taxonomic source for data about microorganisms, which also contains all ITIS data we used previously. The microorganisms data set now contains:
All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria and Protozoa
All ~3,000 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Onygenales, Pneumocystales, Saccharomycetales and Schizosaccharomycetales (covering at least like all species of Aspergillus, Candida, Pneumocystis, Saccharomyces and Trichophyton)
All ~2,000 (sub)species from ~100 other relevant genera, from the kingdoms of Animalia and Plantae (like Strongyloides and Taenia)
All ~15,000 previously accepted names of included (sub)species that have been taxonomically renamed
The responsible author(s) and year of scientific publication
This data is updated annually - check the included version with the new function catalogue_of_life_version().
Due to this change, some mo codes changed (e.g. Streptococcus changed from B_STRPTC to B_STRPT). A translation table is used internally to support older microorganism IDs, so users will not notice this difference.
New function mo_rank() for the taxonomic rank (genus, species, infraspecies, etc.)
New function mo_url() to get the direct URL of a species from the Catalogue of Life
Support for data from WHONET and EARS-Net (European Antimicrobial Resistance Surveillance Network):
first_isolate() and eucast_rules(), all parameters will be filled in automatically.antibiotics data set now contains a column ears_net.as.mo() now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the microorganisms.codes data set.New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
filter_aminoglycosides()
filter_carbapenems()
filter_cephalosporins()
filter_1st_cephalosporins()
filter_2nd_cephalosporins()
filter_3rd_cephalosporins()
filter_4th_cephalosporins()
filter_fluoroquinolones()
filter_glycopeptides()
filter_macrolides()
filter_tetracyclines()The antibiotics data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the antibiotics data set. For example:
septic_patients %>% filter_glycopeptides(result = "R")
# Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R
septic_patients %>% filter_glycopeptides(result = "R", scope = "all")
# Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is RAll ab_* functions are deprecated and replaced by atc_* functions:
ab_property -> atc_property()
ab_name -> atc_name()
ab_official -> atc_official()
ab_trivial_nl -> atc_trivial_nl()
ab_certe -> atc_certe()
ab_umcg -> atc_umcg()
ab_tradenames -> atc_tradenames()These functions use as.atc() internally. The old atc_property has been renamed atc_online_property(). This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class atc or must be coerable to this class. Properties of these classes should start with the same class name, analogous to as.mo() and e.g. mo_genus.
New functions set_mo_source() and get_mo_source() to use your own predefined MO codes as input for as.mo() and consequently all mo_* functions
Support for the upcoming dplyr version 0.8.0
New function guess_ab_col() to find an antibiotic column in a table
New function mo_failures() to review values that could not be coerced to a valid MO code, using as.mo(). This latter function will now only show a maximum of 10 uncoerced values and will refer to mo_failures().
New function mo_uncertainties() to review values that could be coerced to a valid MO code using as.mo(), but with uncertainty.
New function mo_renamed() to get a list of all returned values from as.mo() that have had taxonomic renaming
New function age() to calculate the (patients) age in years
New function age_groups() to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.
New function ggplot_rsi_predict() as well as the base R plot() function can now be used for resistance prediction calculated with resistance_predict():
x <- resistance_predict(septic_patients, col_ab = "amox")
plot(x)
ggplot_rsi_predict(x)Functions filter_first_isolate() and filter_first_weighted_isolate() to shorten and fasten filtering on data sets with antimicrobial results, e.g.:
septic_patients %>% filter_first_isolate(...)
# or
filter_first_isolate(septic_patients, ...)is equal to:
septic_patients %>%
mutate(only_firsts = first_isolate(septic_patients, ...)) %>%
filter(only_firsts == TRUE) %>%
select(-only_firsts)New function availability() to check the number of available (non-empty) results in a data.frame
New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the G-test and more. These are also available (and even easier readable) on our website: https://msberends.gitlab.io/AMR.
eucast_rules():
septic_patients now reflects these changeseucast_rules(..., verbose = TRUE) to get a data set with all changed per bug and drug combination.microorganisms.oldDT, microorganisms.prevDT, microorganisms.unprevDT and microorganismsDT since they were no longer needed and only contained info already available in the microorganisms data setantibiotics data set, from the Pharmaceuticals Community Register of the European Commissionatc_group1_nl and atc_group2_nl from the antibiotics data setatc_ddd() and atc_groups() have been renamed atc_online_ddd() and atc_online_groups(). The old functions are deprecated and will be removed in a future version.guess_mo() is now deprecated in favour of as.mo() and will be removed in future versionsguess_atc() is now deprecated in favour of as.atc() and will be removed in future versionsas.mo():
Now handles incorrect spelling, like i instead of y and f instead of ph:
# mo_fullname() uses as.mo() internally
mo_fullname("Sthafilokockus aaureuz")
#> [1] "Staphylococcus aureus"
mo_fullname("S. klossi")
#> [1] "Staphylococcus kloosii"Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default allow_uncertain = TRUE is equal to uncertainty level 2. Run ?as.mo for more info about these levels.
# equal:
as.mo(..., allow_uncertain = TRUE)
as.mo(..., allow_uncertain = 2)
# also equal:
as.mo(..., allow_uncertain = FALSE)
as.mo(..., allow_uncertain = 0)Using as.mo(..., allow_uncertain = 3) could lead to very unreliable results.
Implemented the latest publication of Becker et al. (2019), for categorising coagulase-negative Staphylococci
All microbial IDs that found are now saved to a local file ~/.Rhistory_mo. Use the new function clean_mo_history() to delete this file, which resets the algorithms.
Incoercible results will now be considered ‘unknown’, MO code UNKNOWN. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:
mo_genus("qwerty", language = "es")
# Warning:
# one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
#> [1] "(género desconocido)"Fix for vector containing only empty values
Finds better results when input is in other languages
Better handling for subspecies
Better handling for Salmonellae, especially the ‘city like’ serovars like Salmonella London
Understanding of highly virulent E. coli strains like EIEC, EPEC and STEC
There will be looked for uncertain results at default - these results will be returned with an informative warning
Manual (help page) now contains more info about the algorithms
Progress bar will be shown when it takes more than 3 seconds to get results
Support for formatted console text
Console will return the percentage of uncoercable input
first_isolate():
septic_patients data set this yielded a difference of 0.15% more isolatescol_patientid), when this parameter was left blankcol_keyantibiotics()), when this parameter was left blankoutput_logical, the function will now always return a logical valuefilter_specimen to specimen_group, although using filter_specimen will still workportion functions, that low counts can influence the outcome and that the portion functions may camouflage this, since they only return the portion (albeit being dependent on the minimum parameter)microorganisms.certe and microorganisms.umcg into microorganisms.codes
mo_taxonomy() now contains the kingdom toois.rsi.eligible() using the new threshold parameterscale_rsi_colours()
mo will now return the top 3 and the unique count, e.g. using summary(mo)
rsi and mic
as.rsi():
"HIGH S" will return S
freq() function):
Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:
Header info is now available as a list, with the header function
The parameter header is now set to TRUE at default, even for markdown
Added header info for class mo to show unique count of families, genera and species
Now honours the decimal.mark setting, which just like format defaults to getOption("OutDec")
The new big.mark parameter will at default be "," when decimal.mark = "." and "." otherwise
Fix for header text where all observations are NA
New parameter droplevels to exclude empty factor levels when input is a factor
Factor levels will be in header when present in input data (maximum of 5)
Fix for using select() on frequency tables
scale_y_percent() now contains the limits parametermdro(), key_antibiotics() and eucast_rules()
resistance_predict() function)as.mic() to support more values ending in (several) zeroes%like%, it will now return the callcount_all to get all available isolates (that like all portion_* and count_* functions also supports summarise and group_by), the old n_rsi is now an alias of count_all
get_locale to determine language for language-dependent output for some mo_* functions. This is now the default value for their language parameter, by which the system language will be used at default.microorganismsDT, microorganisms.prevDT, microorganisms.unprevDT and microorganisms.oldDT to improve the speed of as.mo. They are for reference only, since they are primarily for internal use of as.mo.read.4D to read from the 4D database of the MMB department of the UMCGmo_authors and mo_year to get specific values about the scientific reference of a taxonomic entryFunctions MDRO, BRMO, MRGN and EUCAST_exceptional_phenotypes were renamed to mdro, brmo, mrgn and eucast_exceptional_phenotypes
EUCAST_rules was renamed to eucast_rules, the old function still exists as a deprecated function
Big changes to the eucast_rules function:
rules to specify which rules should be applied (expert rules, breakpoints, others or all)verbose which can be set to TRUE to get very specific messages about which columns and rows were affectedseptic_patients now reflects these changespipe for piperacillin (J01CA12), also to the mdro functionAdded column kingdom to the microorganisms data set, and function mo_kingdom to look up values
Tremendous speed improvement for as.mo (and subsequently all mo_* functions), as empty values wil be ignored a priori
Fewer than 3 characters as input for as.mo will return NA
Function as.mo (and all mo_* wrappers) now supports genus abbreviations with “species” attached
as.mo("E. species") # B_ESCHR
mo_fullname("E. spp.") # "Escherichia species"
as.mo("S. spp") # B_STPHY
mo_fullname("S. species") # "Staphylococcus species"Added parameter combine_IR (TRUE/FALSE) to functions portion_df and count_df, to indicate that all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)
Fix for portion_*(..., as_percent = TRUE) when minimal number of isolates would not be met
Added parameter also_single_tested for portion_* and count_* functions to also include cases where not all antibiotics were tested but at least one of the tested antibiotics includes the target antimicribial interpretation, see ?portion
Using portion_* functions now throws a warning when total available isolate is below parameter minimum
Functions as.mo, as.rsi, as.mic, as.atc and freq will not set package name as attribute anymore
Frequency tables - freq():
Support for grouping variables, test with:
Support for (un)selecting columns:
Check for hms::is.hms
Now prints in markdown at default in non-interactive sessions
No longer adds the factor level column and sorts factors on count again
Support for class difftime
New parameter na, to choose which character to print for empty values
New parameter header to turn the header info off (default when markdown = TRUE)
New parameter title to manually setbthe title of the frequency table
first_isolate now tries to find columns to use as input when parameters are left blank
Improvements for MDRO algorithm (function mdro)
Data set septic_patients is now a data.frame, not a tibble anymore
Removed diacritics from all authors (columns microorganisms$ref and microorganisms.old$ref) to comply with CRAN policy to only allow ASCII characters
Fix for mo_property not working properly
Fix for eucast_rules where some Streptococci would become ceftazidime R in EUCAST rule 4.5
Support for named vectors of class mo, useful for top_freq()
ggplot_rsi and scale_y_percent have breaks parameter
AI improvements for as.mo:
"CRS" -> Stenotrophomonas maltophilia
"CRSM" -> Stenotrophomonas maltophilia
"MSSA" -> Staphylococcus aureus
"MSSE" -> Staphylococcus epidermidis
Fix for join functions
Speed improvement for is.rsi.eligible, now 15-20 times faster
In g.test, when sum(x) is below 1000 or any of the expected values is below 5, Fisher’s Exact Test will be suggested
ab_name will try to fall back on as.atc when no results are found
Removed the addin to view data sets
Percentages will now will rounded more logically (e.g. in freq function)
The data set microorganisms now contains all microbial taxonomic data from ITIS (kingdoms Bacteria, Fungi and Protozoa), the Integrated Taxonomy Information System, available via https://itis.gov. The data set now contains more than 18,000 microorganisms with all known bacteria, fungi and protozoa according ITIS with genus, species, subspecies, family, order, class, phylum and subkingdom. The new data set microorganisms.old contains all previously known taxonomic names from those kingdoms.
New functions based on the existing function mo_property:
mo_phylum, mo_class, mo_order, mo_family, mo_genus, mo_species, mo_subspecies
mo_fullname, mo_shortname
mo_type, mo_gramstain
mo_ref
They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:
mo_gramstain("E. coli")
# [1] "Gram negative"
mo_gramstain("E. coli", language = "de") # German
# [1] "Gramnegativ"
mo_gramstain("E. coli", language = "es") # Spanish
# [1] "Gram negativo"
mo_fullname("S. group A", language = "pt") # Portuguese
# [1] "Streptococcus grupo A"Furthermore, former taxonomic names will give a note about the current taxonomic name:
mo_gramstain("Esc blattae")
# Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
# [1] "Gram negative"Functions count_R, count_IR, count_I, count_SI and count_S to selectively count resistant or susceptible isolates
count_df (which works like portion_df) to get all counts of S, I and R of a data set with antibiotic columns, with support for grouped variablesFunction is.rsi.eligible to check for columns that have valid antimicrobial results, but do not have the rsi class yet. Transform the columns of your raw data with: data %>% mutate_if(is.rsi.eligible, as.rsi)
Functions as.mo and is.mo as replacements for as.bactid and is.bactid (since the microoganisms data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The as.mo function determines microbial IDs using intelligent rules:
as.mo("E. coli")
# [1] B_ESCHR_COL
as.mo("MRSA")
# [1] B_STPHY_AUR
as.mo("S group A")
# [1] B_STRPTC_GRAAnd with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:
thousands_of_E_colis <- rep("E. coli", 25000)
microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s")
# Unit: seconds
# min median max neval
# 0.01817717 0.01843957 0.03878077 100Added parameter reference_df for as.mo, so users can supply their own microbial IDs, name or codes as a reference table
Renamed all previous references to bactid to mo, like:
EUCAST_rules, first_isolate and key_antibiotics
microorganisms and septic_patients
Function labels_rsi_count to print datalabels on a RSI ggplot2 model
Functions as.atc and is.atc to transform/look up antibiotic ATC codes as defined by the WHO. The existing function guess_atc is now an alias of as.atc.
Function ab_property and its aliases: ab_name, ab_tradenames, ab_certe, ab_umcg and ab_trivial_nl
Introduction to AMR as a vignette
Removed clipboard functions as it violated the CRAN policy
Renamed septic_patients$sex to septic_patients$gender
Added three antimicrobial agents to the antibiotics data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)
Added 163 trade names to the antibiotics data set, it now contains 298 different trade names in total, e.g.:
For first_isolate, rows will be ignored when there’s no species available
Function ratio is now deprecated and will be removed in a future release, as it is not really the scope of this package
Fix for as.mic for values ending in zeroes after a real number
Small fix where B. fragilis would not be found in the microorganisms.umcg data set
Added prevalence column to the microorganisms data set
Added parameters minimum and as_percent to portion_df
Support for quasiquotation in the functions series count_* and portions_*, and n_rsi. This allows to check for more than 2 vectors or columns.
Edited ggplot_rsi and geom_rsi so they can cope with count_df. The new fun parameter has value portion_df at default, but can be set to count_df.
Fix for ggplot_rsi when the ggplot2 package was not loaded
Added datalabels function labels_rsi_count to ggplot_rsi
Added possibility to set any parameter to geom_rsi (and ggplot_rsi) so you can set your own preferences
Fix for joins, where predefined suffices would not be honoured
Added parameter quote to the freq function
Added generic function diff for frequency tables
Added longest en shortest character length in the frequency table (freq) header of class character
Support for types (classes) list and matrix for freq
For lists, subsetting is possible:
rsi_df was removed in favour of new functions portion_R, portion_IR, portion_I, portion_SI and portion_S to selectively calculate resistance or susceptibility. These functions are 20 to 30 times faster than the old rsi function. The old function still works, but is deprecated.
portion_df to get all portions of S, I and R of a data set with antibiotic columns, with support for grouped variablesggplot2
geom_rsi, facet_rsi, scale_y_percent, scale_rsi_colours and theme_rsi
ggplot_rsi to apply all above functions on a data set:
septic_patients %>% select(tobr, gent) %>% ggplot_rsi will show portions of S, I and R immediately in a pretty plot?ggplot_rsi
as.bactid and is.bactid to transform/ look up microbial ID’s.guess_bactid is now an alias of as.bactid
kurtosis and skewness that are lacking in base R - they are generic functions and have support for vectors, data.frames and matricesg.test to perform the Χ2 distributed G-test, which use is the same as chisq.test
ratio to transform a vector of values to a preset ratioratio(c(10, 500, 10), ratio = "1:2:1") would return 130, 260, 130%in% or %like% (and give them keyboard shortcuts), or to view the datasets that come with this packagep.symbol to transform p values to their related symbols: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
clipboard_import and clipboard_export as helper functions to quickly copy and paste from/to software like Excel and SPSS. These functions use the clipr package, but are a little altered to also support headless Linux servers (so you can use it in RStudio Server)freq):
rsi (antimicrobial resistance) to use as inputtable to use as input: freq(table(x, y))
hist and plot to use a frequency table as input: hist(freq(df$age))
as.vector, as.data.frame, as_tibble and format
freq(mydata, mycolumn) is the same as mydata %>% freq(mycolumn)
top_freq function to return the top/below n items as vectoroptions(max.print.freq = n) where n is your preset valueresistance_predict and added more examplesseptic_patients data set to better reflect the realitymic and rsi classes now returns all values - use freq to check distributionskey_antibiotics function are now generic: 6 for broadspectrum ABs, 6 for Gram-positive specific and 6 for Gram-negative specific ABsabname function%like% now supports multiple patternsdata.frames with altered console printing to make it look like a frequency table. Because of this, the parameter toConsole is not longer needed.freq where the class of an item would be lostseptic_patients dataset and the column bactid now has the new class "bactid"
microorganisms dataset (especially for Salmonella) and the column bactid now has the new class "bactid"
rsi and mic functions:
as.rsi("<=0.002; S") will return S
as.mic("<=0.002; S") will return <=0.002
as.mic("<= 0.002") now worksrsi and mic do not add the attribute package.version anymore"groups" option for atc_property(..., property). It will return a vector of the ATC hierarchy as defined by the WHO. The new function atc_groups is a convenient wrapper around this.atc_property as it requires the host set by url to be responsivefirst_isolate algorithm to exclude isolates where bacteria ID or genus is unavailable924b62) from the dplyr package v0.7.5 and aboveguess_bactid (now called as.bactid)
yourdata %>% select(genus, species) %>% as.bactid() now also worksn_rsi to count cases where antibiotic test results were available, to be used in conjunction with dplyr::summarise, see ?rsiguess_bactid to determine the ID of a microorganism based on genus/species or known abbreviations like MRSAguess_atc to determine the ATC of an antibiotic based on name, trade name, or known abbreviationsfreq to create frequency tables, with additional info in a headerMDRO to determine Multi Drug Resistant Organisms (MDRO) with support for country-specific guidelines.
BRMO and MRGN are wrappers for Dutch and German guidelines, respectively"points" or "keyantibiotics", see ?first_isolate
tibbles and data.tablesrsi class for vectors that contain only invalid antimicrobial interpretationsablist to antibiotics
bactlist to microorganisms
antibiotics datasetmicroorganisms datasetseptic_patients
join functions%like% to make it case insensitivefirst_isolate and EUCAST_rules column names are now case-insensitiveas.rsi and as.mic now add the package name and version as attributesREADME.md with more examplestestthat package