custom mo update

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dr. M.S. (Matthijs) Berends 2022-12-27 16:03:03 +01:00
parent f619fb683b
commit fe09e9252b
3 changed files with 6 additions and 3 deletions

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Package: AMR
Version: 1.8.2.9070
Version: 1.8.2.9071
Date: 2022-12-27
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

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# AMR 1.8.2.9070
# AMR 1.8.2.9071
*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
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* 20 new antibiotics added and updated all DDDs and ATC codes
* Extended support for antiviral agents (`antivirals` data set), with many new functions
* Now available in 16 languages
* Many new interesting functions, such as `rsi_confidence_interval()` and `mean_amr_distance()`
* Many new interesting functions, such as `rsi_confidence_interval()` and `mean_amr_distance()`, and `add_custom_microorganisms()` to add custom microorganisms to this package
* Many small bug fixes
## New
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We previously relied on our own experience to categorise species into pathogenic groups, but we were very happy to encounter the very recent work of Bartlett *et al.* (2022, DOI [10.1099/mic.0.001269](https://doi.org/10.1099/mic.0.001269)) who extensively studied medical-scientific literature to categorise all bacterial species into groups. See `mo_matching_score()` on how their work was incorporated into the `prevalence` column of the `microorganisms` data set. Using their results, the `as.mo()` and all `mo_*()` functions are now much better capable of converting user input to valid taxonomic records.
The new function `add_custom_microorganisms()` allows users to add custom microorganisms to the `AMR` package.
We also made the following changes regarding the included taxonomy or microorganisms functions:
* Updated full microbiological taxonomy according to the latest daily LPSN data set (December 2022) and latest yearly GBIF taxonomy backbone (November 2022)

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contents:
- "`as.mo`"
- "`mo_property`"
- "`add_custom_microorganisms`"
- "`mo_source`"
- title: "Preparing data: antibiotics"