* Data set `intrinsic_resistant`. This data set contains all bug-drug combinations where the 'bug' is intrinsic resistant to the 'drug' according to the latest EUCAST insights. It contains just two columns: `microorganism` and `antibiotic`.
Curious about which enterococci are actually intrinsic resistant to vancomycin?
* Support for using `dplyr`'s `across()` to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.
* Big speed improvement for interpreting MIC values and disk zone diameters. When interpreting 5,000 MIC values of two antibiotics (10,000 values in total), our benchmarks showed a total run time going from 80.7-85.1 seconds to 1.8-2.0 seconds.
* Function `ab_from_text()` to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses `as.ab()` internally
* [Tidyverse selection helpers](https://tidyselect.r-lib.org/reference/language.html) for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like `dplyr::select()` and `tidyr::pivot_longer()`:
* Added `mo_domain()` as an alias to `mo_kingdom()`
* Added function `filter_penicillins()` to filter isolates on a specific result in any column with a name in the antimicrobial 'penicillins' class (more specific: ATC subgroup *Beta-lactam antibacterials, penicillins*)
* Added official antimicrobial names to all `filter_ab_class()` functions, such as `filter_aminoglycosides()`
* Added antibiotics code "FOX1" for cefoxitin screening (abbreviation "cfsc") to the `antibiotics` data set
* Added parameter `conserve_capped_values` to `as.rsi()` for interpreting MIC values - it makes sure that values starting with "<" (but not "<=") will always return "S" and values starting with ">" (but not ">=") will always return "R". The default behaviour of `as.rsi()` has not changed, so you need to specifically do `as.rsi(..., conserve_capped_values = TRUE)`.
* Big speed improvement for using any function on microorganism codes from earlier package versions (prior to `AMR` v1.2.0), such as `as.mo()`, `mo_name()`, `first_isolate()`, `eucast_rules()`, `mdro()`, etc.
As a consequence, very old microbial codes (from `AMR` v0.5.0 and lower) **are not supported anymore**. Use `as.mo()` on your microorganism names or codes to transform them to current abbreviations used in this package.
* Dramatic improvement of the algorithm behind `as.ab()`, making many more input errors translatable, such as digitalised health care records, using too few or too many vowels or consonants and many more
* Fixed a bug for CLSI 2019 guidelines (using `as.rsi()`), that also included results for animals. It now only contains interpretation guidelines for humans.
* New option `arrows_textangled` for `ggplot_pca()` to indicate whether the text at the end of the arrows should be angled (defaults to `TRUE`, as it was in previous versions)
* Moved primary location of this project from GitLab to [GitHub](https://github.com/msberends/AMR), giving us native support for automated syntax checking without being dependent on external services such as AppVeyor and Travis CI.
* Removed code dependency on all other R packages, making this package fully independent of the development process of others. This is a major code change, but will probably not be noticeable by most users.
Making this package independent of especially the tidyverse (e.g. packages `dplyr` and `tidyr`) tremendously increases sustainability on the long term, since tidyverse functions change quite often. Good for users, but hard for package maintainers. Most of our functions are replaced with versions that only rely on base R, which keeps this package fully functional for many years to come, without requiring a lot of maintenance to keep up with other packages anymore. Another upside it that this package can now be used with all versions of R since R-3.0.0 (April 2013). Our package is being used in settings where the resources are very limited. Fewer dependencies on newer software is helpful for such settings.
* Function `freq()` that was borrowed from the `cleaner` package was removed. Use `cleaner::freq()`, or run `library("cleaner")` before you use `freq()`.
* Printing values of class `mo` or `rsi` in a tibble will no longer be in colour and printing `rsi` in a tibble will show the class `<ord>`, not `<rsi>` anymore. This is purely a visual effect.
* For developers: classes `mo` and `ab` now both also inherit class `character`, to support any data transformation. This change invalidates code that checks for class length == 1.
* Updated the taxonomy of microorganisms to May 2020, using the Catalogue of Life (CoL), the Global Biodiversity Information Facility (GBIF) and the List of Prokaryotic names with Standing in Nomenclature (LPSN, hosted by DSMZ since February 2020). **Note:** a taxonomic update may always impact determination of first isolates (using `first_isolate()`), since some bacterial names might be renamed to other genera or other (sub)species. This is expected behaviour.
* The `eucast_rules()` function no longer applies "other" rules at default that are made available by this package (like setting ampicillin = R when ampicillin + enzyme inhibitor = R). The default input value for `rules` is now `c("breakpoints", "expert")` instead of `"all"`, but this can be changed by the user. To return to the old behaviour, set `options(AMR.eucast_rules = "all")`.
* Fixed a bug where checking antimicrobial results in the original data were not regarded as valid R/SI values
* All "other" rules now apply for all drug combinations in the `antibiotics` data set these two rules:
1. A drug **with** enzyme inhibitor will be set to S if the drug **without** enzyme inhibitor is S
2. A drug **without** enzyme inhibitor will be set to R if the drug **with** enzyme inhibitor is R
This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/avibactam, trimethoprim/sulfamethoxazole, etc.
* Support for all abbreviations of antibiotics and antimycotics used by the Netherlands National Institute for Public Health and the Environment (Rijksinstituut voor Volksgezondheid en Milieu; RIVM)
* 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
* Info printing in functions `eucast_rules()`, `first_isolate()`, `mdro()` and `resistance_predict()` will now at default only print when R is in an interactive mode (i.e. not in RMarkdown)
* Support for the newest [EUCAST Clinical Breakpoint Tables v.10.0](http://www.eucast.org/clinical_breakpoints/), valid from 1 January 2020. This affects translation of MIC and disk zones using `as.rsi()` and inferred resistance and susceptibility using `eucast_rules()`.
* The repository of this package now contains a clean version of the EUCAST and CLSI guidelines from 2011-2020 to translate MIC and disk diffusion values to R/SI: <https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt>. This **allows for machine reading these guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. This file used to process the EUCAST Clinical Breakpoints Excel file [can be found here](https://github.com/msberends/AMR/blob/master/data-raw/read_EUCAST.R).
* 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:
* The `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.
* For in `as.ab()`: support for drugs starting with "co-" like co-amoxiclav, co-trimoxazole, co-trimazine and co-trimazole (thanks to Peter Dutey)
* Changes to the `antibiotics` data set (thanks to Peter Dutey):
* Added more synonyms to colistin, imipenem and piperacillin/tazobactam
* Moved synonyms Rifinah and Rimactazid from rifampicin (`RIF`) to rifampicin/isoniazid (`RFI`). Please note that [the combination rifampicin/isoniazid has no DDDs defined](https://www.whocc.no/atc_ddd_index/?code=J04AM02&showdescription=no), so e.g. `ab_ddd("Rimactazid")` will now return `NA`.
* Moved synonyms Bactrimel and Cotrimazole from sulfamethoxazole (`SMX`) to trimethoprim/sulfamethoxazole (`SXT`)
* Adopted Adeolu *et al.* (2016), [PMID 27620848](https://www.ncbi.nlm.nih.gov/pubmed/27620848) for the `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.
* If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:
```r
if (mo_family(somebugs) == "Enterobacteriaceae") ...
* 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.
* 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).
* This is now the new default guideline for the `mdro()` function
* The new Verbose mode (`mdro(...., 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 agents
* 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](https://en.wikipedia.org/wiki/Levenshtein_distance):
* Renamed all `portion_*` functions to `proportion_*`. All `portion_*` functions are still available as deprecated functions, and will return a warning when used.
* non-EUCAST rules in `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`.
* Rewrote the complete documentation to markdown format, to be able to use the very latest version of the great [Roxygen2](https://roxygen2.r-lib.org/index.html), released in November 2019. This tremously improved the documentation quality, since the rewrite forced us to go over all texts again and make changes where needed.
* Determination 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`:
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`:
```r
# 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':
This 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`](https://github.com/msberends/clean) ([CRAN link](https://cran.r-project.org/package=clean)), 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).
* 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:
* 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:
*`tibble` printing support for classes `rsi`, `mic`, `disk`, `ab``mo`. When using `tibble`s 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.
```r
# (run this on your own console, as this page does not support colour printing)
* Many algorithm improvements for `as.mo()` (of which some led to additions to the `microorganisms` data set). Many thanks to all contributors that helped improving the algorithms.
* Self-learning algorithm - the function now gains experience from previously determined microorganism IDs and learns from it (yielding 80-95% speed improvement for any guess after the first try)
* Big improvement for misspelled input
* These new trivial names known to the field are now understood: meningococcus, gonococcus, pneumococcus
* Updated to the latest taxonomic data (updated to August 2019, from the International Journal of Systematic and Evolutionary Microbiology
* Added support for Viridans Group Streptococci (VGS) and Milleri Group Streptococci (MGS)
* Changed most microorganism IDs to improve readability. For example, the old code `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.
* Fix for using `mo_*` functions where the coercion uncertainties and failures would not be available through `mo_uncertainties()` and `mo_failures()` anymore
* Deprecated the `country` parameter of `mdro()` in favour of the already existing `guideline` parameter to support multiple guidelines within one country
* Added Prof. Dr. Casper Albers as doctoral advisor and added Dr. Judith Fonville, Eric Hazenberg, Dr. Bart Meijer, Dr. Dennis Souverein and Annick Lenglet as contributors
* 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:
* 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
* Support for translation of disk diffusion and MIC values to RSI values (i.e. antimicrobial interpretations). Supported guidelines are EUCAST (2011 to 2019) and CLSI (2011 to 2019). Use `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.
* Added guidelines of the WHO to determine multi-drug resistance (MDR) for TB (`mdr_tb()`) and added a new vignette about MDR. Read this tutorial [here on our website](https://msberends.gitlab.io/AMR/articles/MDR.html).
* 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.
* All output will be translated by using an included translation file which [can be viewed here](https://github.com/msberends/AMR/blob/master/data-raw/translations.tsv)
* 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.
* Removed all hardcoded EUCAST rules and replaced them with a new reference file which [can be viewed here](https://github.com/msberends/AMR/blob/master/data-raw/eucast_rules.tsv)
* Support for R 3.6.0 and later by providing support for [staged install](https://developer.r-project.org/Blog/public/2019/02/14/staged-install/index.html)
We've got a new website: [https://msberends.gitlab.io/AMR](https://msberends.gitlab.io/AMR/) (built with the great [`pkgdown`](https://pkgdown.r-lib.org/))
* Contains the complete manual of this package and all of its functions with an explanation of their parameters
* Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis, import data from WHONET or SPSS and many more.
* 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 ~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*)
* 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.
* Support for data from [WHONET](https://whonet.org/) and [EARS-Net](https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net) (European Antimicrobial Resistance Surveillance Network):
* Exported files from WHONET can be read and used in this package. For functions like `first_isolate()` and `eucast_rules()`, all parameters will be filled in automatically.
* This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the `antibiotics` data set now contains a column `ears_net`.
* The function `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:
```r
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.
* All `ab_*` functions are deprecated and replaced by `atc_*` functions:
```r
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
* 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_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()`:
* Functions `filter_first_isolate()` and `filter_first_weighted_isolate()` to shorten and fasten filtering on data sets with antimicrobial results, e.g.:
* 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.
* Updated EUCAST Clinical breakpoints to [version 9.0 of 1 January 2019](http://www.eucast.org/clinical_breakpoints/), the data set `septic_patients` now reflects these changes
* Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately
* Emphasised in manual that penicillin is meant as benzylpenicillin (ATC [J01CE01](https://www.whocc.no/atc_ddd_index/?code=J01CE01))
* New info is returned when running this function, stating exactly what has been changed or added. Use `eucast_rules(..., verbose = TRUE)` to get a data set with all changed per bug and drug combination.
* Removed data sets `microorganisms.oldDT`, `microorganisms.prevDT`, `microorganisms.unprevDT` and `microorganismsDT` since they were no longer needed and only contained info already available in the `microorganisms` data set
* Added 65 antibiotics to the `antibiotics` data set, from the [Pharmaceuticals Community Register](http://ec.europa.eu/health/documents/community-register/html/atc.htm) of the European Commission
* Removed columns `atc_group1_nl` and `atc_group2_nl` from the `antibiotics` data set
* Functions `atc_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.
* 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.
* 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:
* Fixed a bug where distances between dates would not be calculated right - in the `septic_patients` data set this yielded a difference of 0.15% more isolates
* Will now use a column named like "key(...)ab" or "key(...)antibiotics" for the key antibiotics (parameter `col_keyantibiotics()`), when this parameter was left blank
* A note to the manual pages of the `portion` 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)
* Function `count_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`
* Function `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.
* Data sets `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`.
* Now also applies rules from the EUCAST 'Breakpoint tables for bacteria', version 8.1, 2018, http://www.eucast.org/clinical_breakpoints/ (see Source of the function)
* New parameter `rules` to specify which rules should be applied (expert rules, breakpoints, others or all)
* New parameter `verbose` which can be set to `TRUE` to get very specific messages about which columns and rows were affected
* Better error handling when rules cannot be applied (i.e. new values could not be inserted)
* 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)
* 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`
* Removed diacritics from all authors (columns `microorganisms$ref` and `microorganisms.old$ref`) to comply with CRAN policy to only allow ASCII characters
* 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.
* Extra function `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 variables
* Function `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:
* 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`.
* 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`.
* **BREAKING**: `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.
* **BREAKING**: the methodology for determining first weighted isolates was changed. The antibiotics that are compared between isolates (call *key antibiotics*) to include more first isolates (afterwards called first *weighted* isolates) are now as follows:
* New functions `as.bactid` and `is.bactid` to transform/ look up microbial ID's.
* The existing function `guess_bactid` is now an alias of `as.bactid`
* New Becker classification for *Staphylococcus* to categorise them into Coagulase Negative *Staphylococci* (CoNS) and Coagulase Positve *Staphylococci* (CoPS)
* New Lancefield classification for *Streptococcus* to categorise them into Lancefield groups
* For convience, new descriptive statistical functions `kurtosis` and `skewness` that are lacking in base R - they are generic functions and have support for vectors, data.frames and matrices
* Support for Addins menu in RStudio to quickly insert `%in%` or `%like%` (and give them keyboard shortcuts), or to view the datasets that come with this package
* Function `p.symbol` to transform p values to their related symbols: `0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1`
* Functions `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)
* Column names for the `key_antibiotics` function are now generic: 6 for broadspectrum ABs, 6 for Gram-positive specific and 6 for Gram-negative specific ABs
* Frequency tables are now actual `data.frame`s with altered console printing to make it look like a frequency table. Because of this, the parameter `toConsole` is not longer needed.
* Added `"groups"` option for `atc_property(..., property)`. It will return a vector of the ATC hierarchy as defined by the [WHO](https://www.whocc.no/atc/structure_and_principles/). The new function `atc_groups` is a convenient wrapper around this.
* Build-in host check for `atc_property` as it requires the host set by `url` to be responsive
* Improved `first_isolate` algorithm to exclude isolates where bacteria ID or genus is unavailable
* Fix for warning *hybrid evaluation forced for row_number* ([`924b62`](https://github.com/tidyverse/dplyr/commit/924b62)) from the `dplyr` package v0.7.5 and above
* Function `guess_bactid` to **determine the ID** of a microorganism based on genus/species or known abbreviations like MRSA
* Function `guess_atc` to **determine the ATC** of an antibiotic based on name, trade name, or known abbreviations
* Function `freq` to create **frequency tables**, with additional info in a header
* Function `MDRO` to **determine Multi Drug Resistant Organisms (MDRO)** with support for country-specific guidelines.
* [Exceptional resistances defined by EUCAST](http://www.eucast.org/expert_rules_and_intrinsic_resistance) are also supported instead of countries alone
* Functions `BRMO` and `MRGN` are wrappers for Dutch and German guidelines, respectively
