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custom mo update

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dr. M.S. (Matthijs) Berends 2022-12-27 16:03:03 +01:00
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DESCRIPTION
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Package: AMR Package: AMR
Version: 1.8.2.9070 Version: 1.8.2.9071
Date: 2022-12-27 Date: 2022-12-27
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)

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NEWS.md
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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!)* *(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
@ -12,7 +12,7 @@ This is a new major release of the AMR package, with great new additions but als
* 20 new antibiotics added and updated all DDDs and ATC codes * 20 new antibiotics added and updated all DDDs and ATC codes
* Extended support for antiviral agents (`antivirals` data set), with many new functions * Extended support for antiviral agents (`antivirals` data set), with many new functions
* Now available in 16 languages * 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 * Many small bug fixes
## New ## 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. 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: 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) * 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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_pkgdown.yml
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contents: contents:
- "`as.mo`" - "`as.mo`"
- "`mo_property`" - "`mo_property`"
- "`add_custom_microorganisms`"
- "`mo_source`" - "`mo_source`"
- title: "Preparing data: antibiotics" - title: "Preparing data: antibiotics"