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(v2.1.1.9126) implemented WISCA! Also added top_n_microorganisms() and fixed Python wrapper

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NEWS.md
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# AMR 2.1.1.9125
# AMR 2.1.1.9126
*(this beta version will eventually become v3.0. We're happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using [the instructions here](https://msberends.github.io/AMR/#latest-development-version).)*
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This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the [University of Prince Edward Island's Atlantic Veterinary College](https://www.upei.ca/avc), Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.
## Breaking
* Removed all functions and references that used the deprecated `rsi` class, which were all replaced with their `sir` equivalents over a year ago
* Removed all functions and references that used the deprecated `rsi` class, which were all replaced with their `sir` equivalents two years ago
## New
* **One Health implementation**
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* The `antibiotics` data set contains all veterinary antibiotics, such as pradofloxacin and enrofloxacin. All WHOCC codes for veterinary use have been added as well.
* `ab_atc()` now supports ATC codes of veterinary antibiotics (that all start with "Q")
* `ab_url()` now supports retrieving the WHOCC url of their ATCvet pages
* Support for WISCA antibiograms**
* The `antibiogram()` function now supports creating true Weighted-Incidence Syndromic Combination Antibiograms (WISCA), a powerful Bayesian method for estimating regimen coverage probabilities using pathogen incidence and antimicrobial susceptibility data. WISCA offers improved precision for syndrome-specific treatment, even in datasets with sparse data. A dedicated `wisca()` function is also available for easy usage.
* **Major update to fungal taxonomy and tools for mycologists**
* MycoBank has now been integrated as the primary taxonomic source for fungi. The `microorganisms` data set has been enriched with new columns (`mycobank`, `mycobank_parent`, and `mycobank_renamed_to`) that provide detailed information for fungal species.
* A remarkable addition of over 20,000 new fungal records
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* **Support for `tidymodels`**
* All antimicrobial selectors (such as `aminoglycosides()` and `betalactams()`) are now supported in `tidymodels` packages such as `recipe` and `parsnip`. See for more info [our tutorial](https://msberends.github.io/AMR/articles/AMR_with_tidymodels.html) on using these AMR functions for predictive modelling.
* **Other**
* New function `top_n_microorganisms()` to filter a data set to the top *n* of any taxonomic property, e.g., filter to the top 3 species, filter to any species in the top 5 genera, or filter to the top 3 species in each of the top 5 genera
* New function `mo_group_members()` to retrieve the member microorganisms of a microorganism group. For example, `mo_group_members("Strep group C")` returns a vector of all microorganisms that belong to that group.
## Changed
* SIR interpretation
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* Updated all antibiotic DDDs from WHOCC
* Added over 1,500 trade names for antibiotics
* Fix for using a manual value for `mo_transform` in `antibiogram()`
* Fixed a bug for when `antibiogram()` returns an empty data set
* Fix for mapping 'high level' antibiotics in `as.ab()` (amphotericin B-high, gentamicin-high, kanamycin-high, streptomycin-high, tobramycin-high)
* Improved overall algorithm of `as.ab()` for better performance and accuracy
* Improved overall algorithm of `as.mo()` for better performance and accuracy. Specifically:
* More weight is given to genus and species combinations in cases where the subspecies is miswritten, so that the result will be the correct genus and species
* Genera from the World Health Organization's (WHO) Priority Pathogen List now have the highest prevalence
* Fixed a bug for when `antibiogram()` returns an empty data set
* Fixed a bug for `sir_confidence_interval()` when there are no isolates available
* Updated the prevalence calculation to include genera from the World Health Organization's (WHO) Priority Pathogen List
* Improved algorithm of `first_isolate()` when using the phenotype-based method, to prioritise records with the highest availability of SIR values
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* Added arguments `esbl`, `carbapenemase`, `mecA`, `mecC`, `vanA`, `vanB` to denote column names or logical values indicating presence of these genes (or production of their proteins)
## Other
* Added Dr. Larisse Bolton as contributor for her fantastic implementation of WISCA in a mathematically solid way
* Added Matthew Saab, Dr. Jordan Stull, and Prof. Javier Sanchez as contributors for their tremendous input on veterinary breakpoints and interpretations
* Greatly improved `vctrs` integration, a Tidyverse package working in the background for many Tidyverse functions. For users, this means that functions such as `dplyr`'s `bind_rows()`, `rowwise()` and `c_across()` are now supported for e.g. columns of class `mic`. Despite this, this `AMR` package is still zero-dependent on any other package, including `dplyr` and `vctrs`.
* Greatly updated and expanded documentation
* Added Larisse Bolton, Jordan Stull, Matthew Saab, and Javier Sanchez as contributors, to thank them for their valuable input
* Stopped support for SAS (`.xpt`) files, since their file structure and extremely inefficient and requires more disk space than GitHub allows in a single commit.
## Older Versions
This changelog only contains changes from AMR v3.0 (October 2024) and later.
This changelog only contains changes from AMR v3.0 (February 2025) and later.
* For prior v2 versions, please see [our v2 archive](https://github.com/msberends/AMR/blob/v2.1.1/NEWS.md).
* For prior v1 versions, please see [our v1 archive](https://github.com/msberends/AMR/blob/v1.8.2/NEWS.md).