vignettes/AMR.Rmd
AMR.Rmd
So only 53.1% is suitable for resistance analysis! We can now filter +
So only 53.2% is suitable for resistance analysis! We can now filter on it with the filter() function, also from the dplyr package:
filter()
dplyr
@@ -634,7 +634,7 @@ on it with the data_1st <- data %>% filter_first_isolate() # Including isolates from ICU.
data_1st <- data %>% filter_first_isolate() # Including isolates from ICU.
So we end up with 10,615 isolates for analysis. Now our data looks +
So we end up with 10,640 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: 10,615 -Available: 10,615 (100%, NA: 0 = 0%) +Length: 10,640 +Available: 10,640 (100%, NA: 0 = 0%) Unique: 4
Shortest: 16 Longest: 24
proportion_SI()
data_1st %>% resistance(AMX) -# [1] 0.5501649
Or can be used in conjunction with group_by() and summarise(), both from the dplyr package:
group_by()
summarise()
@@ -1152,19 +1152,19 @@ own: Hospital A -0.5511084 +0.5473815 Hospital B -0.5511442 +0.5484133 Hospital C -0.5606154 +0.5280255 Hospital D -0.5390071 +0.5360920 @@ -1189,23 +1189,23 @@ all isolates available for every group (i.e. values S, I or R): Hospital A -0.5511084 -3248 +0.5473815 +3208 Hospital B -0.5511442 -3627 +0.5484133 +3687 Hospital C -0.5606154 -1625 +0.5280255 +1570 Hospital D -0.5390071 -2115 +0.5360920 +2175 @@ -1230,27 +1230,27 @@ therapies very easily: Escherichia -0.7646154 -0.8782418 -0.9764835 +0.7721220 +0.8792955 +0.9776632 Klebsiella -0.8304239 -0.9118869 -0.9825436 +0.8262411 +0.8953901 +0.9831560 Staphylococcus -0.8040516 -0.8813996 -0.9793738 +0.7907228 +0.8741460 +0.9816613 Streptococcus -0.5365626 +0.5368675 0.0000000 -0.5365626 +0.5368675 @@ -1278,23 +1278,23 @@ classes, use a antibiotic class selector such as Hospital A -55.1% -26.8% +54.7% +26.7% Hospital B -55.1% -26.1% +54.8% +26.7% Hospital C -56.1% -26.2% +52.8% +26.9% Hospital D -53.9% -26.5% +53.6% +24.7% @@ -1410,18 +1410,18 @@ classes) <mic> and <disk>: mic_values <- random_mic(size = 100) mic_values # Class 'mic' -# [1] 64 2 0.01 128 1 8 16 <=0.001 256 -# [10] 0.025 0.005 0.002 256 2 <=0.001 0.5 256 128 -# [19] 16 0.025 0.25 0.002 0.5 8 32 0.125 1 -# [28] 1 0.002 0.125 0.025 32 0.005 0.25 0.0625 0.002 -# [37] 0.01 0.002 32 <=0.001 16 <=0.001 0.125 1 128 -# [46] 0.005 2 0.01 8 0.0625 16 32 0.01 8 -# [55] 256 0.002 0.0625 0.0625 0.005 2 256 4 0.0625 -# [64] 256 4 16 <=0.001 256 0.125 0.002 256 64 -# [73] 4 64 0.0625 0.125 0.25 16 8 1 16 -# [82] 0.125 0.005 128 0.25 16 0.005 256 8 0.01 -# [91] 0.0625 64 4 8 0.01 0.01 128 2 8 -# [100] 8
<mic>
<disk>
mic_values <- random_mic(size = 100) mic_values # Class 'mic' -# [1] 64 2 0.01 128 1 8 16 <=0.001 256 -# [10] 0.025 0.005 0.002 256 2 <=0.001 0.5 256 128 -# [19] 16 0.025 0.25 0.002 0.5 8 32 0.125 1 -# [28] 1 0.002 0.125 0.025 32 0.005 0.25 0.0625 0.002 -# [37] 0.01 0.002 32 <=0.001 16 <=0.001 0.125 1 128 -# [46] 0.005 2 0.01 8 0.0625 16 32 0.01 8 -# [55] 256 0.002 0.0625 0.0625 0.005 2 256 4 0.0625 -# [64] 256 4 16 <=0.001 256 0.125 0.002 256 64 -# [73] 4 64 0.0625 0.125 0.25 16 8 1 16 -# [82] 0.125 0.005 128 0.25 16 0.005 256 8 0.01 -# [91] 0.0625 64 4 8 0.01 0.01 128 2 8 -# [100] 8
# base R: plot(mic_values)
disk_values <- random_disk(size = 100, mo = "E. coli", ab = "cipro") disk_values # Class 'disk' -# [1] 20 22 20 20 22 17 24 28 30 26 26 27 18 26 22 21 23 29 27 21 24 29 19 28 30 -# [26] 21 31 29 27 20 23 18 20 19 19 23 27 29 24 17 29 17 17 22 31 19 25 20 25 19 -# [51] 24 25 21 23 26 28 26 24 17 21 26 23 30 28 19 26 18 28 17 17 27 26 22 26 23 -# [76] 21 18 30 23 25 24 25 31 21 31 20 30 17 23 29 27 17 21 30 19 17 17 21 30 23
# base R: plot(disk_values, mo = "E. coli", ab = "cipro")
head(my_TB_data) # rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin -# 1 S S I R I S -# 2 I S I R R R -# 3 R I I R S I -# 4 S S R S S S -# 5 I S S I R I -# 6 I R S R S S +# 1 I S S S S R +# 2 I S S R I R +# 3 I S S I I S +# 4 R R I R I S +# 5 S S R R I I +# 6 I S S R I R # kanamycin # 1 I # 2 I # 3 S -# 4 R -# 5 I -# 6 I
We can now add the interpretation of MDR-TB to our data set. You can use:
@@ -428,40 +428,40 @@ Unique: 5 1 Mono-resistant -3173 -63.46% -3173 -63.46% +3281 +65.62% +3281 +65.62% 2 Negative -1011 -20.22% -4184 -83.68% +959 +19.18% +4240 +84.80% 3 Multi-drug-resistant -481 -9.62% +425 +8.50% 4665 93.30% 4 Poly-resistant -236 -4.72% -4901 -98.02% +235 +4.70% +4900 +98.00% 5 Extensively drug-resistant -99 -1.98% +100 +2.00% 5000 100.00% diff --git a/articles/PCA.html b/articles/PCA.html index 12b837503..6b42c4806 100644 --- a/articles/PCA.html +++ b/articles/PCA.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/articles/SPSS.html b/articles/SPSS.html index c9d490405..f9602069e 100644 --- a/articles/SPSS.html +++ b/articles/SPSS.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -168,7 +168,7 @@ Dr. Matthijs Berends - 11 December 2022 + 16 December 2022 Source: vignettes/SPSS.Rmd SPSS.Rmd diff --git a/articles/WHONET.html b/articles/WHONET.html index 86473ca5f..3e4da6949 100644 --- a/articles/WHONET.html +++ b/articles/WHONET.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/articles/datasets.html b/articles/datasets.html index dd82bdfe1..f6ede6163 100644 --- a/articles/datasets.html +++ b/articles/datasets.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -166,7 +166,7 @@ Data sets for download / own use - 11 December 2022 + 16 December 2022 Source: vignettes/datasets.Rmd datasets.Rmd @@ -187,7 +187,7 @@ of the data sets look like. microorganisms: Full Microbial Taxonomy -A data set with 48,050 rows and 22 columns, containing the following +A data set with 52,144 rows and 22 columns, containing the following column names:mo, fullname, status, kingdom, phylum, class, order, family, genus, species, subspecies, rank, @@ -196,33 +196,33 @@ column names:mo, fullname, status, kingdomgbif_renamed_to, prevalence and snomed. This data set is in R available as microorganisms, after you load the AMR package. -It was last updated on 11 December 2022 23:14:56 UTC. Find more info +It was last updated on 16 December 2022 15:10:43 UTC. Find more info about the structure of this data set here. Direct download links: Download as original -R Data Structure (RDS) file (1.1 MB) +R Data Structure (RDS) file (1.2 MB) Download as tab-separated -text file (10.4 MB) +text file (11.3 MB) Download as Microsoft -Excel workbook (4.7 MB) +Excel workbook (5 MB) Download as Apache -Feather file (5 MB) +Feather file (5.4 MB) Download as Apache -Parquet file (2.4 MB) +Parquet file (2.6 MB) Download as SAS -data file (46.9 MB) +data file (50.9 MB) Download as IBM -SPSS Statistics data file (15.5 MB) +SPSS Statistics data file (16.8 MB) Download as Stata -DTA file (43.4 MB) +DTA file (47.1 MB) NOTE: The exported files for SAS, SPSS and Stata contain only the first 50 SNOMED codes per record, as their file size would otherwise @@ -265,23 +265,23 @@ Set Name ‘Microoganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: Animalia -1,061 +1,379 Archaea -1,291 +1,314 Bacteria -34,398 +36,478 Fungi -6,852 +7,901 Protozoa -4,447 +5,071 @@ -1042,37 +1042,37 @@ diffusion diameters. Included guidelines are CLSI (2013-2022) and EUCAST intrinsic_resistant: Intrinsic Bacterial Resistance -A data set with 206,832 rows and 2 columns, containing the following +A data set with 134,634 rows and 2 columns, containing the following column names:mo and ab. This data set is in R available as intrinsic_resistant, after you load the AMR package. -It was last updated on 11 December 2022 23:14:56 UTC. Find more info +It was last updated on 16 December 2022 15:10:43 UTC. Find more info about the structure of this data set here. Direct download links: Download as original -R Data Structure (RDS) file (0.1 MB) +R Data Structure (RDS) file (78 kB) Download as tab-separated -text file (7.9 MB) +text file (5.1 MB) Download as Microsoft -Excel workbook (1.9 MB) +Excel workbook (1.3 MB) Download as Apache -Feather file (1.8 MB) +Feather file (1.2 MB) Download as Apache -Parquet file (0.3 MB) +Parquet file (0.2 MB) Download as SAS -data file (17.6 MB) +data file (9.8 MB) Download as IBM -SPSS Statistics data file (11.4 MB) +SPSS Statistics data file (7.4 MB) Download as Stata -DTA file (17.2 MB) +DTA file (9.5 MB) Source diff --git a/articles/index.html b/articles/index.html index 994381533..b7eea2cdb 100644 --- a/articles/index.html +++ b/articles/index.html @@ -1,5 +1,5 @@ -Articles • AMR (for R)Articles • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/articles/resistance_predict.html b/articles/resistance_predict.html index 88ca05bd7..4bfa54732 100644 --- a/articles/resistance_predict.html +++ b/articles/resistance_predict.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/articles/welcome_to_AMR.html b/articles/welcome_to_AMR.html index 44b4c17df..aa6702b35 100644 --- a/articles/welcome_to_AMR.html +++ b/articles/welcome_to_AMR.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -192,7 +192,7 @@ treatment evaluation in any setting. 10.18637/jss.v104.i03) and formed the basis of two PhD theses (DOI 10.33612/diss.177417131 and DOI 10.33612/diss.192486375). -After installing this package, R knows ~48,000 distinct microbial +After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral diff --git a/authors.html b/authors.html index b19dc9c6a..465c3e669 100644 --- a/authors.html +++ b/authors.html @@ -1,5 +1,5 @@ -Authors and Citation • AMR (for R)Authors and Citation • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/index.html b/index.html index 3bb02234b..9e7681414 100644 --- a/index.html +++ b/index.html @@ -20,7 +20,7 @@ - + AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -194,7 +194,7 @@ The AMR package is a free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. This work was published in the Journal of Statistical Software (Volume 104(3); DOI 10.18637/jss.v104.i03) and formed the basis of two PhD theses (DOI 10.33612/diss.177417131 and DOI 10.33612/diss.192486375). -After installing this package, R knows ~48,000 distinct microbial species (updated December 2022) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen, and is being actively and durably maintained by two public healthcare organisations in the Netherlands. +After installing this package, R knows ~52,000 distinct microbial species (updated December 2022) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen, and is being actively and durably maintained by two public healthcare organisations in the Netherlands. Used in 175 countries, translated to 16 languages diff --git a/news/index.html b/news/index.html index 8f6f22618..fc1520d6a 100644 --- a/news/index.html +++ b/news/index.html @@ -1,5 +1,5 @@ -Changelog • AMR (for R)Changelog • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -132,77 +132,70 @@ -AMR 1.8.2.9062 -This version will eventually become v2.0! We’re happy to reach a new major milestone soon! - -Breaking - -Removed all species of the taxonomic kingdom Chromista from the package. This was done for multiple reasons: -CRAN allows packages to be around 5 MB maximum, some packages are exempted but this package is not one of them -Chromista are not relevant when it comes to antimicrobial resistance, thus lacking the primary scope of this package -Chromista are almost never clinically relevant, thus lacking the secondary scope of this package - -The microorganisms no longer relies on the Catalogue of Life, but now primarily on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and is supplemented with 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 1,000 taxonomic names from 2022 already. - -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. -The MO matching score algorithm (mo_matching_score()) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome of as.mo() and any mo_*() function - -Argument combine_IR has been removed from this package (affecting functions count_df(), proportion_df(), and rsi_df() and some plotting functions), since it was replaced with combine_SI three years ago -Interpretation guidelines older than 10 years were removed, the oldest now included guidelines of EUCAST and CLSI are from 2013 -Using units in ab_ddd(..., units = "...") had been deprecated and is now not supported anymore. Use ab_ddd_units() instead. - - -New - -EUCAST 2022 and CLSI 2022 guidelines have been added for as.rsi(). 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. -Support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 16 languages. The automatic language determination will give a note on systems in supported languages. - -All new algorithm for as.mo() (and thus all mo_*() functions) while still following our original set-up as described in our recently published JSS paper (DOI 10.18637/jss.v104.i03). -A new argument keep_synonyms allows to not correct for updated taxonomy, in favour of the now deleted argument allow_uncertain +AMR 1.8.2.9063 +(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 +Microbiological taxonomy (microorganisms data set) updated to 2022 and now based on LPSN and GBIF +Much increased algorithms to translate user input to valid taxonomy +Clinical breakpoints added for EUCAST 2022 and CLSI 2022 +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() -It has increased tremendously in speed and returns generally more consequent results -Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new mo_reset_session() function. -Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net) - - -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. +Hundreds of bug fixes + +New + +Interpretation of MIC and disk diffusion values +EUCAST 2022 and CLSI 2022 guidelines have been added for as.rsi(). 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 +We added support for the following languages: Chinese, Greek, Japanese, Polish, 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 system language. +We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 16 languages and according to download stats used in almost all countries in the world! + + +Microbiological taxonomy +The microorganisms 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 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) * Support for all 1,515 city-like serovars of Salmonella, such as Salmonella Goldcoast. Formally, these are serovars belonging to the S. enterica species, but they are reported with only the name of the genus and the city. For this reason, the serovars are in the subspecies column of the microorganisms data set and “enterica” is in the species column, but the full name does not contain the species name (enterica). * All new algorithm for as.mo() (and thus all mo_*() functions) while still following our original set-up as described in our recently published JSS paper (DOI 10.18637/jss.v104.i03). * A new argument keep_synonyms allows to not correct for updated taxonomy, in favour of the now deleted argument allow_uncertain * It has increased tremendously in speed and returns generally more consequent results * Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new mo_reset_session() function. * Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net) * The MO matching score algorithm (mo_matching_score()) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome of as.mo() and any mo_*() function * Removed all species of the taxonomic kingdom Chromista from the package. This was done for multiple reasons: * CRAN allows packages to be around 5 MB maximum, some packages are exempted but this package is not one of them * Chromista are not relevant when it comes to antimicrobial resistance, thus lacking the primary scope of this package * Chromista are almost never clinically relevant, thus lacking the secondary scope of this package * 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 +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) * Added some missing ATC codes * Updated DDDs and PubChem Compound IDs * Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin) * Antibiotic code “CEI” for ceftolozane/tazobactam has been replaced with “CZT” to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using as.ab() or any of the ab_*() functions. * Support for antimicrobial interpretation of anaerobic bacteria, by adding a ‘placeholder’ code B_ANAER to the microorganisms data set and adding the breakpoints of anaerobics to the rsi_interpretation data set, which is used by as.rsi() for interpretion of MIC and disk diffusion values +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 +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! -Function rsi_confidence_interval() to add confidence intervals in AMR calculation. This is also included in rsi_df() and proportion_df() - + + +Other new functions +Function rsi_confidence_interval() to add confidence intervals in AMR calculation. This is now also included in rsi_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 rsi_interpretation_history() to view the history of previous runs of 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.rsi() was run. Function mo_current() to get the currently valid taxonomic name of a microorganism Function add_custom_antimicrobials() to add custom antimicrobial codes and names to the AMR package - -New and updated entries for the antibiotics data set -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) -Added some missing ATC codes -Updated DDDs and PubChem Compound IDs -Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin) -Antibiotic code “CEI” for ceftolozane/tazobactam has been replaced with “CZT” to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using as.ab() or any of the ab_*() functions. -Support for antimicrobial interpretation of anaerobic bacteria, by adding a ‘placeholder’ code B_ANAER to the microorganisms data set and add the breakpoints of anaerobics to the rsi_interpretation data set, which is used by as.rsi() when interpreting MIC and disk diffusion values - -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 rsi_df() and bug_drug_combinations()), will now return the same data type as the input. -All data sets in this package are now exported as tibble, instead of base R data.frames. Older R versions are still supported. -Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info in this article on our website. -Support for using antibiotic selectors in scoped dplyr verbs (with or without vars()), such as in: ... %>% summarise_at(aminoglycosides(), resistance), see resistance() - + -Changes -Updated the microbiological taxonomy using the latest GBIF backbone (November 2022) and latest LPSN records (11 December 2022) +Changes +Argument combine_IR has been removed from this package (affecting functions count_df(), proportion_df(), and rsi_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 rsi_df() and bug_drug_combinations()), will now return the same data type as the input. +All data sets in this package are now a tibble, instead of base R data.frames. Older R versions are still supported, even if they do not support tibbles. +Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info in this article on our website. For as.rsi(): Fixed certain EUCAST breakpoints for MIC values Allow NA values (e.g. as.rsi(as.disk(NA), ...)) Fix for bug-drug combinations with multiple breakpoints for different body sites Interpretation from MIC and disk zones is now more informative about availability of breakpoints and more robust -The default guideline (EUCAST) can now be changed with options(AMR_guideline = "...") - Removed the as.integer() method for MIC values, since MIC are not integer values and running table() on MIC values consequently failed for not being able to retrieve the level position (as that’s how normally as.integer() on factors work) Fixed determination of Gram stains (mo_gramstain()), since the taxonomic phyla Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes have been renamed to respectively Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota in 2021 @@ -214,9 +207,6 @@ Fixed a bug for mdro() when using similar column names with the Magiorakos guideline Using any random_*() function (such as random_mic()) is now possible by directly calling the package without loading it first: AMR::random_mic(10) -Added Toxoplasma gondii (P_TXPL_GOND) to the microorganisms data set, together with its genus, family, and order -Changed value in column prevalence of the microorganisms data set from 3 to 2 for these genera: Acholeplasma, Alistipes, Alloprevotella, Bergeyella, Borrelia, Brachyspira, Butyricimonas, Cetobacterium, Chlamydia, Chlamydophila, Deinococcus, Dysgonomonas, Elizabethkingia, Empedobacter, Haloarcula, Halobacterium, Halococcus, Myroides, Odoribacter, Ornithobacterium, Parabacteroides, Pedobacter, Phocaeicola, Porphyromonas, Riemerella, Sphingobacterium, Streptobacillus, Tenacibaculum, Terrimonas, Victivallis, Wautersiella, Weeksella - Extended support for the vctrs package, used internally by the tidyverse. This allows to change values of class mic, disk, rsi, mo and ab in tibbles, and to use antibiotic selectors for selecting/filtering, e.g. df[carbapenems() == "R", ] Fix for using info = FALSE in mdro() @@ -234,7 +224,7 @@ Cleaning columns with as.rsi(), as.mic(), or as.disk() will now show the column name in the warning for invalid results -Other +Other 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 Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, and Jonas Salm as contributors, to thank them for their valuable input All R and Rmd files in this project are now styled using the styler package diff --git a/pkgdown.yml b/pkgdown.yml index 589f01a58..5a1686c9c 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -1,5 +1,5 @@ pandoc: 2.19.2 -pkgdown: 2.0.6 +pkgdown: 2.0.7 pkgdown_sha: ~ articles: AMR: AMR.html @@ -11,7 +11,7 @@ articles: datasets: datasets.html resistance_predict: resistance_predict.html welcome_to_AMR: welcome_to_AMR.html -last_built: 2022-12-11T23:19Z +last_built: 2022-12-16T15:14Z 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 63b7d68c2..401830ad3 100644 --- a/reference/AMR-deprecated.html +++ b/reference/AMR-deprecated.html @@ -1,5 +1,5 @@ -Deprecated Functions — AMR-deprecated • AMR (for R)Deprecated Functions — AMR-deprecated • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/AMR.html b/reference/AMR.html index 5d10cb644..f7740fd4c 100644 --- a/reference/AMR.html +++ b/reference/AMR.html @@ -5,7 +5,7 @@ This work was published in the Journal of Statistical Software (Volume 104(3); d ) and formed the basis of two PhD theses (doi:10.33612/diss.177417131 and doi:10.33612/diss.192486375 ). -After installing this package, R knows ~48,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. +After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. This package can be used for: Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF) @@ -25,13 +25,13 @@ Getting LOINC codes of an antibiotic, or getting properties of an antibiotic bas Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI Principal component analysis for AMR -">The AMR Package — AMR • AMR (for R)The AMR Package — AMR • AMR (for R)AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -191,7 +191,7 @@ Principal component analysis for AMR ) and formed the basis of two PhD theses (doi:10.33612/diss.177417131 and doi:10.33612/diss.192486375 ). -After installing this package, R knows ~48,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. +After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. This package can be used for:Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF) Interpreting raw MIC and disk diffusion values, based on any CLSI or EUCAST guideline from the last 10 years diff --git a/reference/Rplot005.png b/reference/Rplot005.png index 11eec1115..56e03bb62 100644 Binary files a/reference/Rplot005.png and b/reference/Rplot005.png differ diff --git a/reference/Rplot006.png b/reference/Rplot006.png index 93004614c..720fe819d 100644 Binary files a/reference/Rplot006.png and b/reference/Rplot006.png differ diff --git a/reference/Rplot007.png b/reference/Rplot007.png index 4f73a3e63..95235c166 100644 Binary files a/reference/Rplot007.png and b/reference/Rplot007.png differ diff --git a/reference/Rplot008.png b/reference/Rplot008.png index 01eaa818a..c2bd05404 100644 Binary files a/reference/Rplot008.png and b/reference/Rplot008.png differ diff --git a/reference/Rplot009.png b/reference/Rplot009.png index d38564722..d5e8ad6ab 100644 Binary files a/reference/Rplot009.png and b/reference/Rplot009.png differ diff --git a/reference/WHOCC.html b/reference/WHOCC.html index 92607c90e..ef1520f02 100644 --- a/reference/WHOCC.html +++ b/reference/WHOCC.html @@ -1,5 +1,5 @@ -WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC • AMR (for R)WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/WHONET.html b/reference/WHONET.html index 7c44879c6..bf88aa815 100644 --- a/reference/WHONET.html +++ b/reference/WHONET.html @@ -1,5 +1,5 @@ -Data Set with 500 Isolates - WHONET Example — WHONET • AMR (for R)Data Set with 500 Isolates - WHONET Example — WHONET • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/ab_from_text.html b/reference/ab_from_text.html index bce18ea50..9b77e939e 100644 --- a/reference/ab_from_text.html +++ b/reference/ab_from_text.html @@ -1,5 +1,5 @@ -Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text • AMR (for R)Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/ab_property.html b/reference/ab_property.html index cf7fd7606..9bd500024 100644 --- a/reference/ab_property.html +++ b/reference/ab_property.html @@ -1,5 +1,5 @@ -Get Properties of an Antibiotic — ab_property • AMR (for R)Get Properties of an Antibiotic — ab_property • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/add_custom_antimicrobials.html b/reference/add_custom_antimicrobials.html index dccca4a6c..971ed0a10 100644 --- a/reference/add_custom_antimicrobials.html +++ b/reference/add_custom_antimicrobials.html @@ -1,5 +1,5 @@ -Add Custom Antimicrobials to This Package — add_custom_antimicrobials • AMR (for R)Add Custom Antimicrobials to This Package — add_custom_antimicrobials • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/age.html b/reference/age.html index 2e750cbb8..1221fe35e 100644 --- a/reference/age.html +++ b/reference/age.html @@ -1,5 +1,5 @@ -Age in Years of Individuals — age • AMR (for R)Age in Years of Individuals — age • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -195,16 +195,16 @@ df #> birth_date age age_exact age_at_y2k -#> 1 1987-02-24 35 35.79452 12 -#> 2 1960-01-10 62 62.91781 39 -#> 3 1981-09-28 41 41.20274 18 -#> 4 1979-02-26 43 43.78904 20 -#> 5 1970-04-15 52 52.65753 29 -#> 6 1953-06-21 69 69.47397 46 -#> 7 1961-04-15 61 61.65753 38 -#> 8 1993-03-18 29 29.73425 6 -#> 9 1936-11-22 86 86.05205 63 -#> 10 1941-07-31 81 81.36438 58 +#> 1 1979-11-08 43 43.10411 20 +#> 2 1945-08-11 77 77.34795 54 +#> 3 1980-04-24 42 42.64658 19 +#> 4 1936-05-24 86 86.56438 63 +#> 5 1975-08-02 47 47.37260 24 +#> 6 1957-01-19 65 65.90685 42 +#> 7 1960-10-22 62 62.15068 39 +#> 8 1955-11-30 67 67.04384 44 +#> 9 1986-01-08 36 36.93699 13 +#> 10 1936-07-04 86 86.45205 63 diff --git a/reference/ggplot_pca.html b/reference/ggplot_pca.html index 7f123323e..6cd9fe6d4 100644 --- a/reference/ggplot_pca.html +++ b/reference/ggplot_pca.html @@ -1,5 +1,5 @@ -PCA Biplot with ggplot2 — ggplot_pca • AMR (for R)PCA Biplot with ggplot2 — ggplot_pca • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/ggplot_rsi.html b/reference/ggplot_rsi.html index b33ec6e43..bd77d50af 100644 --- a/reference/ggplot_rsi.html +++ b/reference/ggplot_rsi.html @@ -1,5 +1,5 @@ -AMR Plots with ggplot2 — ggplot_rsi • AMR (for R)AMR Plots with ggplot2 — ggplot_rsi • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/guess_ab_col.html b/reference/guess_ab_col.html index f7b3cffbb..db83c9e7b 100644 --- a/reference/guess_ab_col.html +++ b/reference/guess_ab_col.html @@ -1,5 +1,5 @@ -Guess Antibiotic Column — guess_ab_col • AMR (for R)Guess Antibiotic Column — guess_ab_col • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/index.html b/reference/index.html index 9b76cf88e..f9c416ba6 100644 --- a/reference/index.html +++ b/reference/index.html @@ -1,5 +1,5 @@ -Function reference • AMR (for R)Function reference • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -355,12 +355,12 @@ microorganisms - Data Set with 48,050 Microorganisms + Data Set with 52,144 Microorganisms microorganisms.codes - Data Set with 5,932 Common Microorganism Codes + Data Set with 5,910 Common Microorganism Codes antibiotics antivirals diff --git a/reference/intrinsic_resistant.html b/reference/intrinsic_resistant.html index a87d8aed3..bcaff7b5c 100644 --- a/reference/intrinsic_resistant.html +++ b/reference/intrinsic_resistant.html @@ -1,5 +1,5 @@ -Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant • AMR (for R)Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -143,7 +143,7 @@ Format - A tibble with 206,832 observations and 2 variables:mo Microorganism ID + A tibble with 134,634 observations and 2 variables:mo Microorganism ID ab Antibiotic ID @@ -161,20 +161,20 @@ Examples intrinsic_resistant -#> # A tibble: 206,832 × 2 -#> mo ab -#> <mo> <ab> -#> 1 B_GRAMP ATM -#> 2 B_GRAMP COL -#> 3 B_GRAMP NAL -#> 4 B_GRAMP PLB -#> 5 B_GRAMP TEM -#> 6 B_ABTRP ATM -#> 7 B_ABTRP COL -#> 8 B_ABTRP NAL -#> 9 B_ABTRP PLB -#> 10 B_ABTRP TEM -#> # … with 206,822 more rows +#> # A tibble: 134,634 × 2 +#> mo ab +#> <mo> <chr> +#> 1 B_GRAMP ATM +#> 2 B_GRAMP COL +#> 3 B_GRAMP NAL +#> 4 B_GRAMP PLB +#> 5 B_GRAMP TEM +#> 6 B_ABTRP ATM +#> 7 B_ABTRP COL +#> 8 B_ABTRP NAL +#> 9 B_ABTRP PLB +#> 10 B_ABTRP TEM +#> # … with 134,624 more rows
vignettes/SPSS.Rmd
SPSS.Rmd
vignettes/datasets.Rmd
datasets.Rmd
microorganisms
A data set with 48,050 rows and 22 columns, containing the following +
A data set with 52,144 rows and 22 columns, containing the following column names:mo, fullname, status, kingdom, phylum, class, order, family, genus, species, subspecies, rank, @@ -196,33 +196,33 @@ column names:mo, fullname, status, kingdomgbif_renamed_to, prevalence and snomed.
This data set is in R available as microorganisms, after you load the AMR package.
AMR
It was last updated on 11 December 2022 23:14:56 UTC. Find more info +
It was last updated on 16 December 2022 15:10:43 UTC. Find more info about the structure of this data set here.
Direct download links:
NOTE: The exported files for SAS, SPSS and Stata contain only the first 50 SNOMED codes per record, as their file size would otherwise @@ -265,23 +265,23 @@ Set Name ‘Microoganism’, OID 2.16.840.1.114222.4.11.1009 (v12). URL: Animalia -1,061 +1,379 Archaea -1,291 +1,314 Bacteria -34,398 +36,478 Fungi -6,852 +7,901 Protozoa -4,447 +5,071 @@ -1042,37 +1042,37 @@ diffusion diameters. Included guidelines are CLSI (2013-2022) and EUCAST intrinsic_resistant: Intrinsic Bacterial Resistance -A data set with 206,832 rows and 2 columns, containing the following +A data set with 134,634 rows and 2 columns, containing the following column names:mo and ab. This data set is in R available as intrinsic_resistant, after you load the AMR package. -It was last updated on 11 December 2022 23:14:56 UTC. Find more info +It was last updated on 16 December 2022 15:10:43 UTC. Find more info about the structure of this data set here. Direct download links: Download as original -R Data Structure (RDS) file (0.1 MB) +R Data Structure (RDS) file (78 kB) Download as tab-separated -text file (7.9 MB) +text file (5.1 MB) Download as Microsoft -Excel workbook (1.9 MB) +Excel workbook (1.3 MB) Download as Apache -Feather file (1.8 MB) +Feather file (1.2 MB) Download as Apache -Parquet file (0.3 MB) +Parquet file (0.2 MB) Download as SAS -data file (17.6 MB) +data file (9.8 MB) Download as IBM -SPSS Statistics data file (11.4 MB) +SPSS Statistics data file (7.4 MB) Download as Stata -DTA file (17.2 MB) +DTA file (9.5 MB) Source diff --git a/articles/index.html b/articles/index.html index 994381533..b7eea2cdb 100644 --- a/articles/index.html +++ b/articles/index.html @@ -1,5 +1,5 @@ -Articles • AMR (for R)Articles • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/articles/resistance_predict.html b/articles/resistance_predict.html index 88ca05bd7..4bfa54732 100644 --- a/articles/resistance_predict.html +++ b/articles/resistance_predict.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/articles/welcome_to_AMR.html b/articles/welcome_to_AMR.html index 44b4c17df..aa6702b35 100644 --- a/articles/welcome_to_AMR.html +++ b/articles/welcome_to_AMR.html @@ -18,7 +18,7 @@ - + @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -192,7 +192,7 @@ treatment evaluation in any setting. 10.18637/jss.v104.i03) and formed the basis of two PhD theses (DOI 10.33612/diss.177417131 and DOI 10.33612/diss.192486375). -After installing this package, R knows ~48,000 distinct microbial +After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral diff --git a/authors.html b/authors.html index b19dc9c6a..465c3e669 100644 --- a/authors.html +++ b/authors.html @@ -1,5 +1,5 @@ -Authors and Citation • AMR (for R)Authors and Citation • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/index.html b/index.html index 3bb02234b..9e7681414 100644 --- a/index.html +++ b/index.html @@ -20,7 +20,7 @@ - + AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -194,7 +194,7 @@ The AMR package is a free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. This work was published in the Journal of Statistical Software (Volume 104(3); DOI 10.18637/jss.v104.i03) and formed the basis of two PhD theses (DOI 10.33612/diss.177417131 and DOI 10.33612/diss.192486375). -After installing this package, R knows ~48,000 distinct microbial species (updated December 2022) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen, and is being actively and durably maintained by two public healthcare organisations in the Netherlands. +After installing this package, R knows ~52,000 distinct microbial species (updated December 2022) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen, and is being actively and durably maintained by two public healthcare organisations in the Netherlands. Used in 175 countries, translated to 16 languages diff --git a/news/index.html b/news/index.html index 8f6f22618..fc1520d6a 100644 --- a/news/index.html +++ b/news/index.html @@ -1,5 +1,5 @@ -Changelog • AMR (for R)Changelog • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -132,77 +132,70 @@ -AMR 1.8.2.9062 -This version will eventually become v2.0! We’re happy to reach a new major milestone soon! - -Breaking - -Removed all species of the taxonomic kingdom Chromista from the package. This was done for multiple reasons: -CRAN allows packages to be around 5 MB maximum, some packages are exempted but this package is not one of them -Chromista are not relevant when it comes to antimicrobial resistance, thus lacking the primary scope of this package -Chromista are almost never clinically relevant, thus lacking the secondary scope of this package - -The microorganisms no longer relies on the Catalogue of Life, but now primarily on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and is supplemented with 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 1,000 taxonomic names from 2022 already. - -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. -The MO matching score algorithm (mo_matching_score()) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome of as.mo() and any mo_*() function - -Argument combine_IR has been removed from this package (affecting functions count_df(), proportion_df(), and rsi_df() and some plotting functions), since it was replaced with combine_SI three years ago -Interpretation guidelines older than 10 years were removed, the oldest now included guidelines of EUCAST and CLSI are from 2013 -Using units in ab_ddd(..., units = "...") had been deprecated and is now not supported anymore. Use ab_ddd_units() instead. - - -New - -EUCAST 2022 and CLSI 2022 guidelines have been added for as.rsi(). 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. -Support for the following languages: Chinese, Greek, Japanese, Polish, Turkish and Ukrainian. We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 16 languages. The automatic language determination will give a note on systems in supported languages. - -All new algorithm for as.mo() (and thus all mo_*() functions) while still following our original set-up as described in our recently published JSS paper (DOI 10.18637/jss.v104.i03). -A new argument keep_synonyms allows to not correct for updated taxonomy, in favour of the now deleted argument allow_uncertain +AMR 1.8.2.9063 +(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 +Microbiological taxonomy (microorganisms data set) updated to 2022 and now based on LPSN and GBIF +Much increased algorithms to translate user input to valid taxonomy +Clinical breakpoints added for EUCAST 2022 and CLSI 2022 +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() -It has increased tremendously in speed and returns generally more consequent results -Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new mo_reset_session() function. -Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net) - - -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. +Hundreds of bug fixes + +New + +Interpretation of MIC and disk diffusion values +EUCAST 2022 and CLSI 2022 guidelines have been added for as.rsi(). 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 +We added support for the following languages: Chinese, Greek, Japanese, Polish, 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 system language. +We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 16 languages and according to download stats used in almost all countries in the world! + + +Microbiological taxonomy +The microorganisms 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 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) * Support for all 1,515 city-like serovars of Salmonella, such as Salmonella Goldcoast. Formally, these are serovars belonging to the S. enterica species, but they are reported with only the name of the genus and the city. For this reason, the serovars are in the subspecies column of the microorganisms data set and “enterica” is in the species column, but the full name does not contain the species name (enterica). * All new algorithm for as.mo() (and thus all mo_*() functions) while still following our original set-up as described in our recently published JSS paper (DOI 10.18637/jss.v104.i03). * A new argument keep_synonyms allows to not correct for updated taxonomy, in favour of the now deleted argument allow_uncertain * It has increased tremendously in speed and returns generally more consequent results * Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new mo_reset_session() function. * Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net) * The MO matching score algorithm (mo_matching_score()) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome of as.mo() and any mo_*() function * Removed all species of the taxonomic kingdom Chromista from the package. This was done for multiple reasons: * CRAN allows packages to be around 5 MB maximum, some packages are exempted but this package is not one of them * Chromista are not relevant when it comes to antimicrobial resistance, thus lacking the primary scope of this package * Chromista are almost never clinically relevant, thus lacking the secondary scope of this package * 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 +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) * Added some missing ATC codes * Updated DDDs and PubChem Compound IDs * Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin) * Antibiotic code “CEI” for ceftolozane/tazobactam has been replaced with “CZT” to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using as.ab() or any of the ab_*() functions. * Support for antimicrobial interpretation of anaerobic bacteria, by adding a ‘placeholder’ code B_ANAER to the microorganisms data set and adding the breakpoints of anaerobics to the rsi_interpretation data set, which is used by as.rsi() for interpretion of MIC and disk diffusion values +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 +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! -Function rsi_confidence_interval() to add confidence intervals in AMR calculation. This is also included in rsi_df() and proportion_df() - + + +Other new functions +Function rsi_confidence_interval() to add confidence intervals in AMR calculation. This is now also included in rsi_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 rsi_interpretation_history() to view the history of previous runs of 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.rsi() was run. Function mo_current() to get the currently valid taxonomic name of a microorganism Function add_custom_antimicrobials() to add custom antimicrobial codes and names to the AMR package - -New and updated entries for the antibiotics data set -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) -Added some missing ATC codes -Updated DDDs and PubChem Compound IDs -Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin) -Antibiotic code “CEI” for ceftolozane/tazobactam has been replaced with “CZT” to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using as.ab() or any of the ab_*() functions. -Support for antimicrobial interpretation of anaerobic bacteria, by adding a ‘placeholder’ code B_ANAER to the microorganisms data set and add the breakpoints of anaerobics to the rsi_interpretation data set, which is used by as.rsi() when interpreting MIC and disk diffusion values - -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 rsi_df() and bug_drug_combinations()), will now return the same data type as the input. -All data sets in this package are now exported as tibble, instead of base R data.frames. Older R versions are still supported. -Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info in this article on our website. -Support for using antibiotic selectors in scoped dplyr verbs (with or without vars()), such as in: ... %>% summarise_at(aminoglycosides(), resistance), see resistance() - + -Changes -Updated the microbiological taxonomy using the latest GBIF backbone (November 2022) and latest LPSN records (11 December 2022) +Changes +Argument combine_IR has been removed from this package (affecting functions count_df(), proportion_df(), and rsi_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 rsi_df() and bug_drug_combinations()), will now return the same data type as the input. +All data sets in this package are now a tibble, instead of base R data.frames. Older R versions are still supported, even if they do not support tibbles. +Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info in this article on our website. For as.rsi(): Fixed certain EUCAST breakpoints for MIC values Allow NA values (e.g. as.rsi(as.disk(NA), ...)) Fix for bug-drug combinations with multiple breakpoints for different body sites Interpretation from MIC and disk zones is now more informative about availability of breakpoints and more robust -The default guideline (EUCAST) can now be changed with options(AMR_guideline = "...") - Removed the as.integer() method for MIC values, since MIC are not integer values and running table() on MIC values consequently failed for not being able to retrieve the level position (as that’s how normally as.integer() on factors work) Fixed determination of Gram stains (mo_gramstain()), since the taxonomic phyla Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes have been renamed to respectively Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota in 2021 @@ -214,9 +207,6 @@ Fixed a bug for mdro() when using similar column names with the Magiorakos guideline Using any random_*() function (such as random_mic()) is now possible by directly calling the package without loading it first: AMR::random_mic(10) -Added Toxoplasma gondii (P_TXPL_GOND) to the microorganisms data set, together with its genus, family, and order -Changed value in column prevalence of the microorganisms data set from 3 to 2 for these genera: Acholeplasma, Alistipes, Alloprevotella, Bergeyella, Borrelia, Brachyspira, Butyricimonas, Cetobacterium, Chlamydia, Chlamydophila, Deinococcus, Dysgonomonas, Elizabethkingia, Empedobacter, Haloarcula, Halobacterium, Halococcus, Myroides, Odoribacter, Ornithobacterium, Parabacteroides, Pedobacter, Phocaeicola, Porphyromonas, Riemerella, Sphingobacterium, Streptobacillus, Tenacibaculum, Terrimonas, Victivallis, Wautersiella, Weeksella - Extended support for the vctrs package, used internally by the tidyverse. This allows to change values of class mic, disk, rsi, mo and ab in tibbles, and to use antibiotic selectors for selecting/filtering, e.g. df[carbapenems() == "R", ] Fix for using info = FALSE in mdro() @@ -234,7 +224,7 @@ Cleaning columns with as.rsi(), as.mic(), or as.disk() will now show the column name in the warning for invalid results -Other +Other 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 Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, and Jonas Salm as contributors, to thank them for their valuable input All R and Rmd files in this project are now styled using the styler package diff --git a/pkgdown.yml b/pkgdown.yml index 589f01a58..5a1686c9c 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -1,5 +1,5 @@ pandoc: 2.19.2 -pkgdown: 2.0.6 +pkgdown: 2.0.7 pkgdown_sha: ~ articles: AMR: AMR.html @@ -11,7 +11,7 @@ articles: datasets: datasets.html resistance_predict: resistance_predict.html welcome_to_AMR: welcome_to_AMR.html -last_built: 2022-12-11T23:19Z +last_built: 2022-12-16T15:14Z 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 63b7d68c2..401830ad3 100644 --- a/reference/AMR-deprecated.html +++ b/reference/AMR-deprecated.html @@ -1,5 +1,5 @@ -Deprecated Functions — AMR-deprecated • AMR (for R)Deprecated Functions — AMR-deprecated • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/AMR.html b/reference/AMR.html index 5d10cb644..f7740fd4c 100644 --- a/reference/AMR.html +++ b/reference/AMR.html @@ -5,7 +5,7 @@ This work was published in the Journal of Statistical Software (Volume 104(3); d ) and formed the basis of two PhD theses (doi:10.33612/diss.177417131 and doi:10.33612/diss.192486375 ). -After installing this package, R knows ~48,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. +After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. This package can be used for: Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF) @@ -25,13 +25,13 @@ Getting LOINC codes of an antibiotic, or getting properties of an antibiotic bas Machine reading the EUCAST and CLSI guidelines from 2011-2020 to translate MIC values and disk diffusion diameters to R/SI Principal component analysis for AMR -">The AMR Package — AMR • AMR (for R)The AMR Package — AMR • AMR (for R)AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -191,7 +191,7 @@ Principal component analysis for AMR ) and formed the basis of two PhD theses (doi:10.33612/diss.177417131 and doi:10.33612/diss.192486375 ). -After installing this package, R knows ~48,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. +After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data. This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation. This package can be used for:Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF) Interpreting raw MIC and disk diffusion values, based on any CLSI or EUCAST guideline from the last 10 years diff --git a/reference/Rplot005.png b/reference/Rplot005.png index 11eec1115..56e03bb62 100644 Binary files a/reference/Rplot005.png and b/reference/Rplot005.png differ diff --git a/reference/Rplot006.png b/reference/Rplot006.png index 93004614c..720fe819d 100644 Binary files a/reference/Rplot006.png and b/reference/Rplot006.png differ diff --git a/reference/Rplot007.png b/reference/Rplot007.png index 4f73a3e63..95235c166 100644 Binary files a/reference/Rplot007.png and b/reference/Rplot007.png differ diff --git a/reference/Rplot008.png b/reference/Rplot008.png index 01eaa818a..c2bd05404 100644 Binary files a/reference/Rplot008.png and b/reference/Rplot008.png differ diff --git a/reference/Rplot009.png b/reference/Rplot009.png index d38564722..d5e8ad6ab 100644 Binary files a/reference/Rplot009.png and b/reference/Rplot009.png differ diff --git a/reference/WHOCC.html b/reference/WHOCC.html index 92607c90e..ef1520f02 100644 --- a/reference/WHOCC.html +++ b/reference/WHOCC.html @@ -1,5 +1,5 @@ -WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC • AMR (for R)WHOCC: WHO Collaborating Centre for Drug Statistics Methodology — WHOCC • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/WHONET.html b/reference/WHONET.html index 7c44879c6..bf88aa815 100644 --- a/reference/WHONET.html +++ b/reference/WHONET.html @@ -1,5 +1,5 @@ -Data Set with 500 Isolates - WHONET Example — WHONET • AMR (for R)Data Set with 500 Isolates - WHONET Example — WHONET • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/ab_from_text.html b/reference/ab_from_text.html index bce18ea50..9b77e939e 100644 --- a/reference/ab_from_text.html +++ b/reference/ab_from_text.html @@ -1,5 +1,5 @@ -Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text • AMR (for R)Retrieve Antimicrobial Drug Names and Doses from Clinical Text — ab_from_text • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/ab_property.html b/reference/ab_property.html index cf7fd7606..9bd500024 100644 --- a/reference/ab_property.html +++ b/reference/ab_property.html @@ -1,5 +1,5 @@ -Get Properties of an Antibiotic — ab_property • AMR (for R)Get Properties of an Antibiotic — ab_property • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/add_custom_antimicrobials.html b/reference/add_custom_antimicrobials.html index dccca4a6c..971ed0a10 100644 --- a/reference/add_custom_antimicrobials.html +++ b/reference/add_custom_antimicrobials.html @@ -1,5 +1,5 @@ -Add Custom Antimicrobials to This Package — add_custom_antimicrobials • AMR (for R)Add Custom Antimicrobials to This Package — add_custom_antimicrobials • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/age.html b/reference/age.html index 2e750cbb8..1221fe35e 100644 --- a/reference/age.html +++ b/reference/age.html @@ -1,5 +1,5 @@ -Age in Years of Individuals — age • AMR (for R)Age in Years of Individuals — age • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -195,16 +195,16 @@ df #> birth_date age age_exact age_at_y2k -#> 1 1987-02-24 35 35.79452 12 -#> 2 1960-01-10 62 62.91781 39 -#> 3 1981-09-28 41 41.20274 18 -#> 4 1979-02-26 43 43.78904 20 -#> 5 1970-04-15 52 52.65753 29 -#> 6 1953-06-21 69 69.47397 46 -#> 7 1961-04-15 61 61.65753 38 -#> 8 1993-03-18 29 29.73425 6 -#> 9 1936-11-22 86 86.05205 63 -#> 10 1941-07-31 81 81.36438 58 +#> 1 1979-11-08 43 43.10411 20 +#> 2 1945-08-11 77 77.34795 54 +#> 3 1980-04-24 42 42.64658 19 +#> 4 1936-05-24 86 86.56438 63 +#> 5 1975-08-02 47 47.37260 24 +#> 6 1957-01-19 65 65.90685 42 +#> 7 1960-10-22 62 62.15068 39 +#> 8 1955-11-30 67 67.04384 44 +#> 9 1986-01-08 36 36.93699 13 +#> 10 1936-07-04 86 86.45205 63 diff --git a/reference/ggplot_pca.html b/reference/ggplot_pca.html index 7f123323e..6cd9fe6d4 100644 --- a/reference/ggplot_pca.html +++ b/reference/ggplot_pca.html @@ -1,5 +1,5 @@ -PCA Biplot with ggplot2 — ggplot_pca • AMR (for R)PCA Biplot with ggplot2 — ggplot_pca • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/ggplot_rsi.html b/reference/ggplot_rsi.html index b33ec6e43..bd77d50af 100644 --- a/reference/ggplot_rsi.html +++ b/reference/ggplot_rsi.html @@ -1,5 +1,5 @@ -AMR Plots with ggplot2 — ggplot_rsi • AMR (for R)AMR Plots with ggplot2 — ggplot_rsi • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/guess_ab_col.html b/reference/guess_ab_col.html index f7b3cffbb..db83c9e7b 100644 --- a/reference/guess_ab_col.html +++ b/reference/guess_ab_col.html @@ -1,5 +1,5 @@ -Guess Antibiotic Column — guess_ab_col • AMR (for R)Guess Antibiotic Column — guess_ab_col • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 diff --git a/reference/index.html b/reference/index.html index 9b76cf88e..f9c416ba6 100644 --- a/reference/index.html +++ b/reference/index.html @@ -1,5 +1,5 @@ -Function reference • AMR (for R)Function reference • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -355,12 +355,12 @@ microorganisms - Data Set with 48,050 Microorganisms + Data Set with 52,144 Microorganisms microorganisms.codes - Data Set with 5,932 Common Microorganism Codes + Data Set with 5,910 Common Microorganism Codes antibiotics antivirals diff --git a/reference/intrinsic_resistant.html b/reference/intrinsic_resistant.html index a87d8aed3..bcaff7b5c 100644 --- a/reference/intrinsic_resistant.html +++ b/reference/intrinsic_resistant.html @@ -1,5 +1,5 @@ -Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant • AMR (for R)Data Set with Bacterial Intrinsic Resistance — intrinsic_resistant • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9062 + 1.8.2.9063 @@ -143,7 +143,7 @@ Format - A tibble with 206,832 observations and 2 variables:mo Microorganism ID + A tibble with 134,634 observations and 2 variables:mo Microorganism ID ab Antibiotic ID @@ -161,20 +161,20 @@ Examples intrinsic_resistant -#> # A tibble: 206,832 × 2 -#> mo ab -#> <mo> <ab> -#> 1 B_GRAMP ATM -#> 2 B_GRAMP COL -#> 3 B_GRAMP NAL -#> 4 B_GRAMP PLB -#> 5 B_GRAMP TEM -#> 6 B_ABTRP ATM -#> 7 B_ABTRP COL -#> 8 B_ABTRP NAL -#> 9 B_ABTRP PLB -#> 10 B_ABTRP TEM -#> # … with 206,822 more rows +#> # A tibble: 134,634 × 2 +#> mo ab +#> <mo> <chr> +#> 1 B_GRAMP ATM +#> 2 B_GRAMP COL +#> 3 B_GRAMP NAL +#> 4 B_GRAMP PLB +#> 5 B_GRAMP TEM +#> 6 B_ABTRP ATM +#> 7 B_ABTRP COL +#> 8 B_ABTRP NAL +#> 9 B_ABTRP PLB +#> 10 B_ABTRP TEM +#> # … with 134,624 more rows
intrinsic_resistant
A data set with 206,832 rows and 2 columns, containing the following +
A data set with 134,634 rows and 2 columns, containing the following column names:mo and ab.
This data set is in R available as intrinsic_resistant, after you load the AMR package.
After installing this package, R knows ~48,000 distinct microbial +
After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral diff --git a/authors.html b/authors.html index b19dc9c6a..465c3e669 100644 --- a/authors.html +++ b/authors.html @@ -1,5 +1,5 @@ -
The AMR package is a free and open-source R package with zero dependencies to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. Our aim is to provide a standard for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting.
This work was published in the Journal of Statistical Software (Volume 104(3); DOI 10.18637/jss.v104.i03) and formed the basis of two PhD theses (DOI 10.33612/diss.177417131 and DOI 10.33612/diss.192486375).
After installing this package, R knows ~48,000 distinct microbial species (updated December 2022) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen, and is being actively and durably maintained by two public healthcare organisations in the Netherlands.
After installing this package, R knows ~52,000 distinct microbial species (updated December 2022) and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. The integral breakpoint guidelines from CLSI and EUCAST are included from the last 10 years. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice Foundation and University Medical Center Groningen, and is being actively and durably maintained by two public healthcare organisations in the Netherlands.
This version will eventually become v2.0! We’re happy to reach a new major milestone soon!
microorganisms.old
status
"accepted"
"synonym"
mo_matching_score()
as.mo()
mo_*()
combine_IR
count_df()
proportion_df()
rsi_df()
combine_SI
units
ab_ddd(..., units = "...")
ab_ddd_units()
as.rsi()
eucast_rules()
keep_synonyms
allow_uncertain
(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
antivirals
rsi_confidence_interval()
mean_amr_distance()
mo_reset_session()
EUCAST 2022 and CLSI 2022 guidelines have been added for as.rsi(). 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").
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 languages: Chinese, Greek, Japanese, Polish, 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 system language.
We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 16 languages and according to download stats used in almost all countries in the world!
The microorganisms 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 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) * Support for all 1,515 city-like serovars of Salmonella, such as Salmonella Goldcoast. Formally, these are serovars belonging to the S. enterica species, but they are reported with only the name of the genus and the city. For this reason, the serovars are in the subspecies column of the microorganisms data set and “enterica” is in the species column, but the full name does not contain the species name (enterica). * All new algorithm for as.mo() (and thus all mo_*() functions) while still following our original set-up as described in our recently published JSS paper (DOI 10.18637/jss.v104.i03). * A new argument keep_synonyms allows to not correct for updated taxonomy, in favour of the now deleted argument allow_uncertain * It has increased tremendously in speed and returns generally more consequent results * Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new mo_reset_session() function. * Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net) * The MO matching score algorithm (mo_matching_score()) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome of as.mo() and any mo_*() function * Removed all species of the taxonomic kingdom Chromista from the package. This was done for multiple reasons: * CRAN allows packages to be around 5 MB maximum, some packages are exempted but this package is not one of them * Chromista are not relevant when it comes to antimicrobial resistance, thus lacking the primary scope of this package * Chromista are almost never clinically relevant, thus lacking the secondary scope of this package * 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.
subspecies
species
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: * 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) * Added some missing ATC codes * Updated DDDs and PubChem Compound IDs * Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin) * Antibiotic code “CEI” for ceftolozane/tazobactam has been replaced with “CZT” to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using as.ab() or any of the ab_*() functions. * Support for antimicrobial interpretation of anaerobic bacteria, by adding a ‘placeholder’ code B_ANAER to the microorganisms data set and adding the breakpoints of anaerobics to the rsi_interpretation data set, which is used by as.rsi() for interpretion of MIC and disk diffusion values
antibiotics
as.ab()
ab_*()
B_ANAER
rsi_interpretation
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.
av
ab
as.av()
av_name()
av_atc()
av_synonyms()
av_from_text()
rsi_interpretation_history()
mo_current()
data.frame
data.table::data.table
janitor::tabyl
tibble::tibble
tsibble::tsibble
bug_drug_combinations()
tibble
NA
as.rsi(as.disk(NA), ...)
options(AMR_guideline = "...")
as.integer()
table()
factor
mo_gramstain()
mdro()
random_*()
random_mic()
AMR::random_mic(10)
P_TXPL_GOND
prevalence
vctrs
mic
disk
rsi
mo
df[carbapenems() == "R", ]
info = FALSE
as.mic()
as.disk()
styler
After installing this package, R knows ~48,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
After installing this package, R knows ~52,000 distinct microbial species and all ~600 antibiotic, antimycotic and antiviral drugs by name and code (including ATC, EARS-NET, LOINC and SNOMED CT), and knows all about valid R/SI and MIC values. It supports any data format, including WHONET/EARS-Net data.
This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained and free software; you can freely use and distribute it for both personal and commercial (but not patent) purposes under the terms of the GNU General Public License version 2.0 (GPL-2), as published by the Free Software Foundation.
This package can be used for:
Reference for the taxonomy of microorganisms, since the package contains all microbial (sub)species from the List of Prokaryotic names with Standing in Nomenclature (LPSN) and the Global Biodiversity Information Facility (GBIF)
Interpreting raw MIC and disk diffusion values, based on any CLSI or EUCAST guideline from the last 10 years
microorganisms.codes
A tibble with 206,832 observations and 2 variables:
mo Microorganism ID
A tibble with 134,634 observations and 2 variables:
ab Antibiotic ID
intrinsic_resistant -#> # A tibble: 206,832 × 2 -#> mo ab -#> <mo> <ab> -#> 1 B_GRAMP ATM -#> 2 B_GRAMP COL -#> 3 B_GRAMP NAL -#> 4 B_GRAMP PLB -#> 5 B_GRAMP TEM -#> 6 B_ABTRP ATM -#> 7 B_ABTRP COL -#> 8 B_ABTRP NAL -#> 9 B_ABTRP PLB -#> 10 B_ABTRP TEM -#> # … with 206,822 more rows +#> # A tibble: 134,634 × 2 +#> mo ab +#> <mo> <chr> +#> 1 B_GRAMP ATM +#> 2 B_GRAMP COL +#> 3 B_GRAMP NAL +#> 4 B_GRAMP PLB +#> 5 B_GRAMP TEM +#> 6 B_ABTRP ATM +#> 7 B_ABTRP COL +#> 8 B_ABTRP NAL +#> 9 B_ABTRP PLB +#> 10 B_ABTRP TEM +#> # … with 134,624 more rows