vignettes/AMR.Rmd
AMR.Rmd
So only 61.5% is suitable for resistance analysis! We can now filter +
So only 61.2% is suitable for resistance analysis! We can now filter on it with the filter() function, also from the dplyr package:
filter()
dplyr
@@ -644,11 +644,11 @@ on it with the data_1st <- data %>% filter_first_isolate()
data_1st <- data %>% filter_first_isolate()
So we end up with 12 300 isolates for analysis. Now our data looks +
So we end up with 12 241 isolates for analysis. Now our data looks like:
head(data_1st)
Time for the analysis!
data_1st %>% freq(genus, species)
Frequency table
Class: character -Length: 12,300 -Available: 12,300 (100%, NA: 0 = 0%) +Length: 12,241 +Available: 12,241 (100%, NA: 0 = 0%) Unique: 4
Shortest: 16 Longest: 24
proportion_SI()
data_1st %>% resistance(AMX) -# [1] 0.59
Or can be used in conjunction with group_by() and summarise(), both from the dplyr package:
group_by()
summarise()
@@ -1162,19 +1169,19 @@ own: Hospital A -0.5931973 +0.5864297 Hospital B -0.5891020 +0.5778776 Hospital C -0.5969416 +0.5783004 Hospital D -0.5818110 +0.5938144 @@ -1199,23 +1206,23 @@ all isolates available for every group (i.e. values S, I or R): Hospital A -0.5931973 -3675 +0.5864297 +3714 Hospital B -0.5891020 -4276 +0.5778776 +4231 Hospital C -0.5969416 -1831 +0.5783004 +1871 Hospital D -0.5818110 -2518 +0.5938144 +2425 @@ -1240,27 +1247,27 @@ therapies very easily: Escherichia -0.6659801 -0.6620323 -0.8884312 +0.6667810 +0.6520322 +0.8814955 Klebsiella -0.6442167 -0.6610542 -0.8755490 +0.6349085 +0.6692073 +0.8833841 Staphylococcus -0.6523353 -0.6640891 -0.8892669 +0.6599815 +0.6497994 +0.8707189 Streptococcus -0.4650667 +0.4787291 0.0000000 -0.4650667 +0.4787291 @@ -1288,23 +1295,23 @@ classes, use a antibiotic class selector such as Hospital A -59.3% -37.6% +58.6% +36.7% Hospital B -58.9% -37.3% +57.8% +36.4% Hospital C -59.7% -36.4% +57.8% +37.7% Hospital D -58.2% -36.3% +59.4% +36.5% @@ -1420,16 +1427,18 @@ classes) <mic> and <disk>: mic_values <- random_mic(size = 100) mic_values # Class 'mic' -# [1] 4 0.5 0.0625 0.25 64 0.025 0.002 128 0.25 16 -# [11] 0.0625 0.002 32 32 64 >=256 0.005 0.25 32 2 -# [21] 4 0.002 0.01 128 >=256 0.0625 2 0.002 4 0.001 -# [31] 4 8 128 0.001 0.0625 32 0.01 0.002 64 16 -# [41] 8 16 0.25 0.25 0.001 64 128 0.025 0.01 2 -# [51] 0.01 1 0.0625 8 4 8 0.25 128 0.002 0.001 -# [61] 1 2 0.25 0.5 128 0.125 0.125 1 0.5 0.001 -# [71] 0.002 0.002 16 64 0.0625 2 0.0625 0.025 0.5 0.002 -# [81] 4 >=256 0.01 32 0.025 0.002 0.125 128 8 4 -# [91] 0.005 4 1 4 128 >=256 0.01 8 128 32
<mic>
<disk>
mic_values <- random_mic(size = 100) mic_values # Class 'mic' -# [1] 4 0.5 0.0625 0.25 64 0.025 0.002 128 0.25 16 -# [11] 0.0625 0.002 32 32 64 >=256 0.005 0.25 32 2 -# [21] 4 0.002 0.01 128 >=256 0.0625 2 0.002 4 0.001 -# [31] 4 8 128 0.001 0.0625 32 0.01 0.002 64 16 -# [41] 8 16 0.25 0.25 0.001 64 128 0.025 0.01 2 -# [51] 0.01 1 0.0625 8 4 8 0.25 128 0.002 0.001 -# [61] 1 2 0.25 0.5 128 0.125 0.125 1 0.5 0.001 -# [71] 0.002 0.002 16 64 0.0625 2 0.0625 0.025 0.5 0.002 -# [81] 4 >=256 0.01 32 0.025 0.002 0.125 128 8 4 -# [91] 0.005 4 1 4 128 >=256 0.01 8 128 32
# base R: plot(mic_values)
disk_values <- random_disk(size = 100, mo = "E. coli", ab = "cipro") disk_values # Class 'disk' -# [1] 31 21 27 24 29 23 31 18 22 25 23 27 28 21 26 20 18 30 29 28 25 25 22 17 27 -# [26] 22 26 30 24 25 27 18 28 20 25 30 28 22 22 31 30 27 25 22 26 21 30 31 20 27 -# [51] 31 21 22 19 21 19 29 29 19 31 30 18 18 19 27 18 18 27 29 28 21 23 18 29 20 -# [76] 17 20 18 22 25 21 20 28 26 27 22 19 30 19 18 29 28 29 23 19 21 18 25 19 17
# base R: plot(disk_values, mo = "E. coli", ab = "cipro")
head(my_TB_data) # rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin -# 1 S R I I S I -# 2 S S S S I R -# 3 I S R R I S -# 4 R S S I S R -# 5 S I S I S I -# 6 R S R R R S +# 1 S I S R I S +# 2 S R I I R I +# 3 S S S S R R +# 4 S R S I I R +# 5 S I R S R I +# 6 S R I R R S # kanamycin -# 1 S +# 1 I # 2 S -# 3 R -# 4 S -# 5 S +# 3 S +# 4 R +# 5 I # 6 S
We can now add the interpretation of MDR-TB to our data set. You can use:
# Groups (n=4, named as 'order'): diff --git a/articles/SPSS.html b/articles/SPSS.html index 34249824..3cd7089a 100644 --- a/articles/SPSS.html +++ b/articles/SPSS.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 @@ -178,7 +178,7 @@ Dr. Matthijs Berends - 11 February 2023 + 12 February 2023 Source: vignettes/SPSS.Rmd SPSS.Rmd diff --git a/articles/WHONET.html b/articles/WHONET.html index 962996cd..753be116 100644 --- a/articles/WHONET.html +++ b/articles/WHONET.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/articles/datasets.html b/articles/datasets.html index 3ce5f361..59a6256f 100644 --- a/articles/datasets.html +++ b/articles/datasets.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 @@ -176,7 +176,7 @@ Data sets for download / own use - 11 February 2023 + 12 February 2023 Source: vignettes/datasets.Rmd datasets.Rmd diff --git a/articles/index.html b/articles/index.html index 0bc3581b..e5d4ecd9 100644 --- a/articles/index.html +++ b/articles/index.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/articles/resistance_predict.html b/articles/resistance_predict.html index a7c0f41d..ce8ddbba 100644 --- a/articles/resistance_predict.html +++ b/articles/resistance_predict.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/articles/welcome_to_AMR.html b/articles/welcome_to_AMR.html index 029581e9..03ef291c 100644 --- a/articles/welcome_to_AMR.html +++ b/articles/welcome_to_AMR.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/authors.html b/authors.html index 997ec434..610cf2b0 100644 --- a/authors.html +++ b/authors.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/index.html b/index.html index 9a65a3f2..b2c92695 100644 --- a/index.html +++ b/index.html @@ -42,7 +42,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 @@ -210,7 +210,7 @@ Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names. -With the help of contributors from all corners of the world, the AMR package is available in English, Czech, Chinese, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Polish, Portuguese, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages. +With the help of contributors from all corners of the world, the AMR package is available in English, Czech, Chinese, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages. diff --git a/news/index.html b/news/index.html index 39913b24..caf93d3b 100644 --- a/news/index.html +++ b/news/index.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 @@ -142,7 +142,7 @@ -AMR 1.8.2.9118 +AMR 1.8.2.9119 (this beta version will eventually become v2.0! We’re happy to reach a new major milestone soon!) This is a new major release of the AMR package, with great new additions but also some breaking changes for current users. These are all listed below. TL;DR @@ -156,31 +156,31 @@ Now available in 20 languages Many small bug fixes -New +New -SIR vs. RSI +SIR vs. RSI For this milestone version, we replaced all mentions of RSI with SIR, to comply with what is actually being commonly used in the field of clinical microbiology when it comes to this tri-form regarding AMR. While existing functions such as as.rsi(), rsi_df() and ggplot_rsi() still work, their replacements as.sir(), sir_df(), ggplot_sir() are now the current functions for AMR data analysis. A warning will be thrown once a session to remind users about this. The data set rsi_translation is now called clinical_breakpoints to better reflect its content. The ‘RSI functions’ will be removed in a future version, but not before late 2023 / early 2024. -New antibiogram function +New antibiogram function With the new antibiogram() function, users can now generate traditional, combined, syndromic, and even weighted-incidence syndromic combination antibiograms (WISCA). With this, we follow the logic in the previously described work of Klinker et al. (2021, DOI 10.1177/20499361211011373) and Barbieri et al. (2021, DOI 10.1186/s13756-021-00939-2). The help page for antibiogram() extensively elaborates on use cases, and antibiogram() also supports printing in R Markdown and Quarto, with support for 20 languages. Furthermore, different plotting methods were implemented to allow for graphical visualisations as well. -Interpretation of MIC and disk diffusion values +Interpretation of MIC and disk diffusion values The clinical breakpoints and intrinsic resistance of EUCAST 2022 and CLSI 2022 have been added for as.sir(). EUCAST 2022 (v12.0) is now the new default guideline for all MIC and disks diffusion interpretations, and for eucast_rules() to apply EUCAST Expert Rules. The default guideline (EUCAST) can now be changed with the new AMR_guideline option, such as: options(AMR_guideline = "CLSI 2020"). Interpretation guidelines older than 10 years were removed, the oldest now included guidelines of EUCAST and CLSI are from 2013. -Supported languages +Supported languages We added support for the following ten languages: Chinese (simplified), Czech, Finnish, Greek, Japanese, Norwegian (bokmål), Polish, Romanian, Turkish and Ukrainian. All antibiotic names are now available in these languages, and the AMR package will automatically determine a supported language based on the user’s system language. We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 20 languages in total, and according to download stats used in almost all countries in the world! -Microbiological taxonomy +Microbiological taxonomy The microorganisms data set no longer relies on the Catalogue of Life, but on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and is supplemented with the ‘backbone taxonomy’ from the Global Biodiversity Information Facility (GBIF). The structure of this data set has changed to include separate LPSN and GBIF identifiers. Almost all previous MO codes were retained. It contains over 1,400 taxonomic names from 2022. 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) 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. @@ -204,7 +204,7 @@ The microorganisms.old data set was removed, and all previously accepted names are now included in the microorganisms data set. A new column status contains "accepted" for currently accepted names and "synonym" for taxonomic synonyms; currently invalid names. All previously accepted names now have a microorganisms ID and - if available - an LPSN, GBIF and SNOMED CT identifier. -Antibiotic agents and selectors +Antibiotic agents and selectors The new function add_custom_antimicrobials() allows users to add custom antimicrobial codes and names to the AMR package. The antibiotics data set was greatly updated: The following 20 antibiotics have been added (also includes the new J01RA ATC group): azithromycin/fluconazole/secnidazole (AFC), cefepime/amikacin (CFA), cefixime/ornidazole (CEO), ceftriaxone/beta-lactamase inhibitor (CEB), ciprofloxacin/metronidazole (CIM), ciprofloxacin/ornidazole (CIO), ciprofloxacin/tinidazole (CIT), furazidin (FUR), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), lascufloxacin (LSC), levofloxacin/ornidazole (LEO), nemonoxacin (NEM), norfloxacin/metronidazole (NME), norfloxacin/tinidazole (NTI), ofloxacin/ornidazole (OOR), oteseconazole (OTE), rifampicin/ethambutol/isoniazid (REI), sarecycline (SRC), tetracycline/oleandomycin (TOL), and thioacetazone (TAT) @@ -216,14 +216,14 @@ Also, we added support for using antibiotic selectors in scoped dplyr verbs (with or without using vars()), such as in: ... %>% summarise_at(aminoglycosides(), resistance), please see resistance() for examples. -Antiviral agents +Antiviral agents We now added extensive support for antiviral agents! For the first time, the AMR package has extensive support for antiviral drugs and to work with their names, codes and other data in any way. The antivirals data set has been extended with 18 new drugs (also from the new J05AJ ATC group) and now also contains antiviral identifiers and LOINC codes A new data type av (antivirals) has been added, which is functionally similar to ab for antibiotics Functions as.av(), av_name(), av_atc(), av_synonyms(), av_from_text() have all been added as siblings to their ab_*() equivalents -Other new functions +Other new functions Function sir_confidence_interval() to add confidence intervals in AMR calculation. This is now also included in sir_df() and proportion_df(). Function mean_amr_distance() to calculate the mean AMR distance. The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand. Function sir_interpretation_history() to view the history of previous runs of as.sir() (previously as.rsi()). This returns a ‘logbook’ with the selected guideline, reference table and specific interpretation of each row in a data set on which as.sir() was run. @@ -232,7 +232,7 @@ -Changes +Changes Argument combine_IR has been removed from this package (affecting functions count_df(), proportion_df(), and sir_df() and some plotting functions), since it was replaced with combine_SI three years ago Using units in ab_ddd(..., units = "...") had been deprecated for some time and is now not supported anymore. Use ab_ddd_units() instead. Support for data.frame-enhancing R packages, more specifically: data.table::data.table, janitor::tabyl, tibble::tibble, and tsibble::tsibble. AMR package functions that have a data set as output (such as sir_df() and bug_drug_combinations()), will now return the same data type as the input. @@ -272,7 +272,7 @@ Fix for using g.test() with zeroes in a 2x2 table -Other +Other Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, Andrew Norgan, Jonas Salm, and Anita Williams as contributors, to thank them for their valuable input New website to make use of the new Bootstrap 5 and pkgdown 2.0. The website now contains results for all examples and will be automatically regenerated with every change to our repository, using GitHub Actions All R and Rmd files in this project are now styled using the styler package diff --git a/pkgdown.yml b/pkgdown.yml index 1bc79153..d671b203 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -11,7 +11,7 @@ articles: datasets: datasets.html resistance_predict: resistance_predict.html welcome_to_AMR: welcome_to_AMR.html -last_built: 2023-02-11T21:33Z +last_built: 2023-02-12T10:25Z urls: reference: https://msberends.github.io/AMR/reference article: https://msberends.github.io/AMR/articles diff --git a/reference/AMR-deprecated.html b/reference/AMR-deprecated.html index ba37ff18..4d222e8a 100644 --- a/reference/AMR-deprecated.html +++ b/reference/AMR-deprecated.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/AMR-options.html b/reference/AMR-options.html index b807ab02..1da517b8 100644 --- a/reference/AMR-options.html +++ b/reference/AMR-options.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/AMR.html b/reference/AMR.html index 949227d2..4e99fa68 100644 --- a/reference/AMR.html +++ b/reference/AMR.html @@ -18,7 +18,7 @@ The AMR package is available in English, Chinese, Danish, Dutch, French, German, AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/Rplot005.png b/reference/Rplot005.png index 54f172bf..c51e4d0a 100644 Binary files a/reference/Rplot005.png and b/reference/Rplot005.png differ diff --git a/reference/Rplot006.png b/reference/Rplot006.png index 34f3ebe1..1edabe08 100644 Binary files a/reference/Rplot006.png and b/reference/Rplot006.png differ diff --git a/reference/Rplot007.png b/reference/Rplot007.png index b3ea75c1..429f6772 100644 Binary files a/reference/Rplot007.png and b/reference/Rplot007.png differ diff --git a/reference/Rplot008.png b/reference/Rplot008.png index 714cd378..cec26e02 100644 Binary files a/reference/Rplot008.png and b/reference/Rplot008.png differ diff --git a/reference/Rplot009.png b/reference/Rplot009.png index 35e97632..2765cd1e 100644 Binary files a/reference/Rplot009.png and b/reference/Rplot009.png differ diff --git a/reference/WHOCC.html b/reference/WHOCC.html index a166a10d..a2b9b7e6 100644 --- a/reference/WHOCC.html +++ b/reference/WHOCC.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/WHONET.html b/reference/WHONET.html index 8e553dd7..a69155b9 100644 --- a/reference/WHONET.html +++ b/reference/WHONET.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/ab_from_text.html b/reference/ab_from_text.html index 68db08cb..a523bad1 100644 --- a/reference/ab_from_text.html +++ b/reference/ab_from_text.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/ab_property.html b/reference/ab_property.html index 25934137..0b967d45 100644 --- a/reference/ab_property.html +++ b/reference/ab_property.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/add_custom_antimicrobials.html b/reference/add_custom_antimicrobials.html index f1c4dbee..af84ab56 100644 --- a/reference/add_custom_antimicrobials.html +++ b/reference/add_custom_antimicrobials.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/add_custom_microorganisms.html b/reference/add_custom_microorganisms.html index ecc776f8..89f59569 100644 --- a/reference/add_custom_microorganisms.html +++ b/reference/add_custom_microorganisms.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 diff --git a/reference/age.html b/reference/age.html index e4fbe4e3..e5cb028b 100644 --- a/reference/age.html +++ b/reference/age.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9118 + 1.8.2.9119 @@ -205,16 +205,16 @@ df #> birth_date age age_exact age_at_y2k -#> 1 1937-01-20 86 86.06027 62 -#> 2 1954-10-05 68 68.35342 45 -#> 3 1988-04-16 34 34.82466 11 -#> 4 1969-09-13 53 53.41370 30 -#> 5 1948-10-22 74 74.30685 51 -#> 6 1981-07-08 41 41.59726 18 -#> 7 1985-11-10 37 37.25479 14 -#> 8 1977-10-25 45 45.29863 22 -#> 9 1966-02-01 57 57.02740 33 -#> 10 1963-11-17 59 59.23562 36 +#> 1 1973-02-10 50 50.00548 26 +#> 2 1996-11-25 26 26.21644 3 +#> 3 1944-11-18 78 78.23562 55 +#> 4 1953-05-17 69 69.74247 46 +#> 5 1947-10-24 75 75.30411 52 +#> 6 1946-10-16 76 76.32603 53 +#> 7 1990-07-02 32 32.61644 9 +#> 8 1967-10-18 55 55.32055 32 +#> 9 1974-09-23 48 48.38904 25 +#> 10 1978-11-08 44 44.26301 21
vignettes/SPSS.Rmd
SPSS.Rmd
vignettes/datasets.Rmd
datasets.Rmd
Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.
With the help of contributors from all corners of the world, the AMR package is available in English, Czech, Chinese, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Polish, Portuguese, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
AMR
With the help of contributors from all corners of the world, the AMR package is available in English, Czech, Chinese, Danish, Dutch, Finnish, French, German, Greek, Italian, Japanese, Norwegian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish, and Ukrainian. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
(this beta version will eventually become v2.0! We’re happy to reach a new major milestone soon!)
This is a new major release of the AMR package, with great new additions but also some breaking changes for current users. These are all listed below.
TL;DR
For this milestone version, we replaced all mentions of RSI with SIR, to comply with what is actually being commonly used in the field of clinical microbiology when it comes to this tri-form regarding AMR.
While existing functions such as as.rsi(), rsi_df() and ggplot_rsi() still work, their replacements as.sir(), sir_df(), ggplot_sir() are now the current functions for AMR data analysis. A warning will be thrown once a session to remind users about this. The data set rsi_translation is now called clinical_breakpoints to better reflect its content.
as.rsi()
rsi_df()
ggplot_rsi()
as.sir()
sir_df()
ggplot_sir()
rsi_translation
clinical_breakpoints
The ‘RSI functions’ will be removed in a future version, but not before late 2023 / early 2024.
With the new antibiogram() function, users can now generate traditional, combined, syndromic, and even weighted-incidence syndromic combination antibiograms (WISCA). With this, we follow the logic in the previously described work of Klinker et al. (2021, DOI 10.1177/20499361211011373) and Barbieri et al. (2021, DOI 10.1186/s13756-021-00939-2).
antibiogram()
The help page for antibiogram() extensively elaborates on use cases, and antibiogram() also supports printing in R Markdown and Quarto, with support for 20 languages.
Furthermore, different plotting methods were implemented to allow for graphical visualisations as well.
The clinical breakpoints and intrinsic resistance of EUCAST 2022 and CLSI 2022 have been added for as.sir(). EUCAST 2022 (v12.0) is now the new default guideline for all MIC and disks diffusion interpretations, and for eucast_rules() to apply EUCAST Expert Rules. The default guideline (EUCAST) can now be changed with the new AMR_guideline option, such as: options(AMR_guideline = "CLSI 2020").
eucast_rules()
AMR_guideline
options(AMR_guideline = "CLSI 2020")
Interpretation guidelines older than 10 years were removed, the oldest now included guidelines of EUCAST and CLSI are from 2013.
We added support for the following ten languages: Chinese (simplified), Czech, Finnish, Greek, Japanese, Norwegian (bokmål), Polish, Romanian, Turkish and Ukrainian. All antibiotic names are now available in these languages, and the AMR package will automatically determine a supported language based on the user’s system language.
We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 20 languages in total, and according to download stats used in almost all countries in the world!
The microorganisms data set no longer relies on the Catalogue of Life, but on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and is supplemented with the ‘backbone taxonomy’ from the Global Biodiversity Information Facility (GBIF). The structure of this data set has changed to include separate LPSN and GBIF identifiers. Almost all previous MO codes were retained. It contains over 1,400 taxonomic names from 2022.
microorganisms
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) 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.
mo_matching_score()
prevalence
as.mo()
mo_*()
The new function add_custom_microorganisms() allows users to add custom microorganisms to the AMR package.
add_custom_microorganisms()
microorganisms.old
status
"accepted"
"synonym"
The new function add_custom_antimicrobials() allows users to add custom antimicrobial codes and names to the AMR package.
add_custom_antimicrobials()
The antibiotics data set was greatly updated:
antibiotics
Also, we added support for using antibiotic selectors in scoped dplyr verbs (with or without using vars()), such as in: ... %>% summarise_at(aminoglycosides(), resistance), please see resistance() for examples.
vars()
... %>% summarise_at(aminoglycosides(), resistance)
resistance()
We now added extensive support for antiviral agents! For the first time, the AMR package has extensive support for antiviral drugs and to work with their names, codes and other data in any way.
antivirals
av
ab
as.av()
av_name()
av_atc()
av_synonyms()
av_from_text()
ab_*()
sir_confidence_interval()
proportion_df()
mean_amr_distance()
sir_interpretation_history()
combine_IR
count_df()
combine_SI
units
ab_ddd(..., units = "...")
ab_ddd_units()
data.frame
data.table::data.table
janitor::tabyl
tibble::tibble
tsibble::tsibble
bug_drug_combinations()
g.test()
styler
kurtosis(rnorm(10000)) -#> [1] 2.985188 +#> [1] 2.983574 kurtosis(rnorm(10000), excess = TRUE) -#> [1] 0.01268259 +#> [1] 0.07041612