head(my_TB_data) #> rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin -#> 1 S R R I I R -#> 2 I R R I S I -#> 3 I S I R R I -#> 4 R R I R I S -#> 5 R S I I I S -#> 6 I S I S I R +#> 1 S S I R I I +#> 2 I I R R S R +#> 3 I I R R S R +#> 4 I S I S R S +#> 5 R R R S S I +#> 6 I I R S S I #> kanamycin #> 1 S -#> 2 I +#> 2 R #> 3 R -#> 4 R +#> 4 I #> 5 I -#> 6 I
We can now add the interpretation of MDR-TB to our data set. You can use:
@@ -455,40 +455,40 @@ Unique: 5 1 Mono-resistant -3187 -63.74% -3187 -63.74% +3280 +65.60% +3280 +65.60% 2 Negative -1017 -20.34% -4204 -84.08% +920 +18.40% +4200 +84.00% 3 Multi-drug-resistant -456 -9.12% -4660 -93.20% +459 +9.18% +4659 +93.18% 4 Poly-resistant -230 -4.60% -4890 -97.80% +244 +4.88% +4903 +98.06% 5 Extensively drug-resistant -110 -2.20% +97 +1.94% 5000 100.00% diff --git a/articles/PCA.html b/articles/PCA.html index 093a1514..2e35bb00 100644 --- a/articles/PCA.html +++ b/articles/PCA.html @@ -38,7 +38,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 @@ -307,7 +307,7 @@ function: #> [1] "Caryophanales" "Enterobacterales" "Lactobacillales" "Pseudomonadales" #> Importance of components: #> PC1 PC2 PC3 PC4 PC5 PC6 PC7 -#> Standard deviation 2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 1.232e-16 +#> Standard deviation 2.1539 1.6807 0.6138 0.33879 0.20808 0.03140 9.577e-17 #> Proportion of Variance 0.5799 0.3531 0.0471 0.01435 0.00541 0.00012 0.000e+00 #> Cumulative Proportion 0.5799 0.9330 0.9801 0.99446 0.99988 1.00000 1.000e+00
#> Groups (n=4, named as 'order'): diff --git a/articles/WHONET.html b/articles/WHONET.html index 8070485c..1b8ddeff 100644 --- a/articles/WHONET.html +++ b/articles/WHONET.html @@ -38,7 +38,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/articles/datasets.html b/articles/datasets.html index 5259fee1..50a5b0ff 100644 --- a/articles/datasets.html +++ b/articles/datasets.html @@ -38,7 +38,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 @@ -904,14 +904,14 @@ inhibitors clinical_breakpoints: Interpretation from MIC values & disk diameters to SIR -A data set with 28 885 rows and 12 columns, containing the following +A data set with 29 747 rows and 12 columns, containing the following column names:guideline, type, method, site, mo, rank_index, ab, ref_tbl, disk_dose, breakpoint_S, breakpoint_R, and uti. This data set is in R available as clinical_breakpoints, after you load the AMR package. -It was last updated on 12 July 2023 10:41:25 UTC. Find more info +It was last updated on 12 July 2023 14:04:48 UTC. Find more info about the structure of this data set here. Direct download links: @@ -919,7 +919,7 @@ about the structure of this data set tab-separated -text file (2.2 MB) +text file (2.3 MB) Download as Microsoft Excel workbook (1.3 MB) @@ -928,16 +928,16 @@ Excel workbook (1.3 MB) Feather file (1.2 MB) Download as Apache -Parquet file (87 kB) +Parquet file (96 kB) Download as SAS -transport (XPT) file (7.7 MB) +transport (XPT) file (7.9 MB) Download as IBM -SPSS Statistics data file (4.4 MB) +SPSS Statistics data file (4.6 MB) Download as Stata -DTA file (7.6 MB) +DTA file (7.8 MB) Source @@ -959,7 +959,7 @@ diffusion diameters. Included guidelines are CLSI (2011-2023) and EUCAST - + @@ -988,8 +988,8 @@ diffusion diameters. Included guidelines are CLSI (2011-2023) and EUCAST human DISK -B_ACHRMB_DNTR -Achromobacter denitrificans +B_ACHRMB_XYLS +Achromobacter xylosoxidans 2 MEM Meropenem @@ -1004,8 +1004,8 @@ diffusion diameters. Included guidelines are CLSI (2011-2023) and EUCAST human MIC -B_ACHRMB_DNTR -Achromobacter denitrificans +B_ACHRMB_XYLS +Achromobacter xylosoxidans 2 MEM Meropenem @@ -1020,8 +1020,8 @@ diffusion diameters. Included guidelines are CLSI (2011-2023) and EUCAST human DISK -B_ACHRMB_DNTR -Achromobacter denitrificans +B_ACHRMB_XYLS +Achromobacter xylosoxidans 2 SXT Trimethoprim/sulfamethoxazole @@ -1036,8 +1036,8 @@ diffusion diameters. Included guidelines are CLSI (2011-2023) and EUCAST human MIC -B_ACHRMB_DNTR -Achromobacter denitrificans +B_ACHRMB_XYLS +Achromobacter xylosoxidans 2 SXT Trimethoprim/sulfamethoxazole @@ -1052,8 +1052,8 @@ diffusion diameters. Included guidelines are CLSI (2011-2023) and EUCAST human DISK -B_ACHRMB_DNTR -Achromobacter denitrificans +B_ACHRMB_XYLS +Achromobacter xylosoxidans 2 TZP Piperacillin/tazobactam @@ -1068,8 +1068,8 @@ diffusion diameters. Included guidelines are CLSI (2011-2023) and EUCAST human MIC -B_ACHRMB_DNTR -Achromobacter denitrificans +B_ACHRMB_XYLS +Achromobacter xylosoxidans 2 TZP Piperacillin/tazobactam @@ -2046,13 +2046,13 @@ reality and can be used to practise AMR data analysis. microorganisms.groups: Species Groups and Microbiological Complexes -A data set with 448 rows and 4 columns, containing the following +A data set with 507 rows and 4 columns, containing the following column names:mo_group, mo, mo_group_name, and mo_name. This data set is in R available as microorganisms.groups, after you load the AMR package. -It was last updated on 12 July 2023 10:41:25 UTC. Find more info +It was last updated on 12 July 2023 14:04:48 UTC. Find more info about the structure of this data set here. Direct download links: @@ -2060,25 +2060,25 @@ about the structure of this data set tab-separated -text file (42 kB) +text file (48 kB) Download as Microsoft -Excel workbook (18 kB) +Excel workbook (20 kB) Download as Apache -Feather file (17 kB) +Feather file (18 kB) Download as Apache -Parquet file (12 kB) +Parquet file (13 kB) Download as SAS transport (XPT) file (0 kB) Download as IBM -SPSS Statistics data file (54 kB) +SPSS Statistics data file (62 kB) Download as Stata -DTA file (68 kB) +DTA file (79 kB) Source diff --git a/articles/index.html b/articles/index.html index c9fd5aef..96e238f1 100644 --- a/articles/index.html +++ b/articles/index.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/articles/other_pkg.html b/articles/other_pkg.html index 11293db8..22ef12af 100644 --- a/articles/other_pkg.html +++ b/articles/other_pkg.html @@ -38,7 +38,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/articles/resistance_predict.html b/articles/resistance_predict.html index 97ef051e..069365c5 100644 --- a/articles/resistance_predict.html +++ b/articles/resistance_predict.html @@ -38,7 +38,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/articles/welcome_to_AMR.html b/articles/welcome_to_AMR.html index 6e8b0894..b09f7541 100644 --- a/articles/welcome_to_AMR.html +++ b/articles/welcome_to_AMR.html @@ -38,7 +38,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/authors.html b/authors.html index 3323bd51..c251356e 100644 --- a/authors.html +++ b/authors.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/index.html b/index.html index b9ef70a8..48dce39a 100644 --- a/index.html +++ b/index.html @@ -42,7 +42,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/news/index.html b/news/index.html index 5c79c7c6..23e89eb7 100644 --- a/news/index.html +++ b/news/index.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 @@ -159,9 +159,9 @@ -AMR 2.0.0.9035 +AMR 2.0.0.9038 -New +New Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added for as.sir(). EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretations The EUCAST dosage guideline of v13.0 has been added to the dosage data set ECOFF: the clinical_breakpoints data set now contains epidemiological cut-off (ECOFF) values. These ECOFFs can be used for MIC/disk interpretation using as.sir(..., breakpoint_type = "ECOFF"), which is an important new addition for veterinary microbiology. @@ -176,7 +176,7 @@ Added microbial codes for Gram-negative/positive anaerobic bacteria -Changed +Changed Updated algorithm of as.mo() by giving more weight to fungi mo_rank() now returns NA for ‘unknown’ microorganisms (B_ANAER, B_ANAER-NEG, B_ANAER-POS, B_GRAMN, B_GRAMP, F_FUNGUS, F_YEAST, and UNKNOWN) diff --git a/pkgdown.yml b/pkgdown.yml index 1148f115..8d041839 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -11,7 +11,7 @@ articles: other_pkg: other_pkg.html resistance_predict: resistance_predict.html welcome_to_AMR: welcome_to_AMR.html -last_built: 2023-07-12T10:46Z +last_built: 2023-07-12T14:08Z 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 081b4f30..6e793564 100644 --- a/reference/AMR-deprecated.html +++ b/reference/AMR-deprecated.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/AMR-options.html b/reference/AMR-options.html index 0ac8f320..a73cb528 100644 --- a/reference/AMR-options.html +++ b/reference/AMR-options.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/AMR.html b/reference/AMR.html index ff728b18..f8f87744 100644 --- a/reference/AMR.html +++ b/reference/AMR.html @@ -5,14 +5,14 @@ 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 ~52 000 microorganisms (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 SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. 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. +After installing this package, R knows ~52 000 microorganisms (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 SIR and MIC values. The integral clinical breakpoint guidelines from CLSI and EUCAST are included, even with epidemiological cut-off (ECOFF) values. 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. The AMR package is available in English, Chinese, Czech, 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.">The AMR Package — AMR • AMR (for R)Data Set with 444 Microorganisms In Species Groups — microorganisms.groups • AMR (for R)Data Set with 507 Microorganisms In Species Groups — microorganisms.groups • AMR (for R) @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 @@ -154,7 +154,7 @@ - Data Set with 444 Microorganisms In Species Groups + Data Set with 507 Microorganisms In Species Groups Source: R/data.R microorganisms.groups.Rd @@ -170,7 +170,7 @@ Format - A tibble with 444 observations and 4 variables:mo_group ID of the species group / microbiological complex + A tibble with 507 observations and 4 variables:mo_group ID of the species group / microbiological complex mo ID of the microorganism belonging in the species group / microbiological complex mo_group_name Name of the species group / microbiological complex, as retrieved with mo_name() mo_name Name of the microorganism belonging in the species group / microbiological complex, as retrieved with mo_name() diff --git a/reference/microorganisms.html b/reference/microorganisms.html index 59ef390f..bc57f761 100644 --- a/reference/microorganisms.html +++ b/reference/microorganisms.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/mo_matching_score.html b/reference/mo_matching_score.html index 2851c53f..296f475d 100644 --- a/reference/mo_matching_score.html +++ b/reference/mo_matching_score.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/mo_property.html b/reference/mo_property.html index 5667732c..62e314ec 100644 --- a/reference/mo_property.html +++ b/reference/mo_property.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/mo_source.html b/reference/mo_source.html index 3063dfcc..9a21ddf6 100644 --- a/reference/mo_source.html +++ b/reference/mo_source.html @@ -12,7 +12,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/pca.html b/reference/pca.html index b1440fb7..745e2aab 100644 --- a/reference/pca.html +++ b/reference/pca.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/plot.html b/reference/plot.html index edb8d9e9..61784490 100644 --- a/reference/plot.html +++ b/reference/plot.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/proportion.html b/reference/proportion.html index 8d7320b1..22ca2bab 100644 --- a/reference/proportion.html +++ b/reference/proportion.html @@ -12,7 +12,7 @@ resistance() should be used to calculate resistance, susceptibility() should be AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/random.html b/reference/random.html index cb6de50a..0d3ed3c0 100644 --- a/reference/random.html +++ b/reference/random.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/resistance_predict.html b/reference/resistance_predict.html index 5bf64999..e7551fc4 100644 --- a/reference/resistance_predict.html +++ b/reference/resistance_predict.html @@ -10,7 +10,7 @@ AMR (for R) - 2.0.0.9035 + 2.0.0.9038 diff --git a/reference/skewness.html b/reference/skewness.html index 8063e9ce..164862fc 100644 --- a/reference/skewness.html +++ b/reference/skewness.html @@ -12,7 +12,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu AMR (for R) - 2.0.0.9035 + 2.0.0.9038 @@ -198,7 +198,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu Examples skewness(runif(1000)) -#> [1] 0.07297999 +#> [1] -0.0634746
clinical_breakpoints
A data set with 28 885 rows and 12 columns, containing the following +
A data set with 29 747 rows and 12 columns, containing the following column names:guideline, type, method, site, mo, rank_index, ab, ref_tbl, disk_dose, breakpoint_S, breakpoint_R, and uti.
This data set is in R available as clinical_breakpoints, after you load the AMR package.
AMR
It was last updated on 12 July 2023 10:41:25 UTC. Find more info +
It was last updated on 12 July 2023 14:04:48 UTC. Find more info about the structure of this data set here.
Direct download links:
microorganisms.groups
A data set with 448 rows and 4 columns, containing the following +
A data set with 507 rows and 4 columns, containing the following column names:mo_group, mo, mo_group_name, and mo_name.
This data set is in R available as microorganisms.groups, after you load the AMR package.
as.sir()
dosage
as.sir(..., breakpoint_type = "ECOFF")
as.mo()
mo_rank()
NA
B_ANAER
B_ANAER-NEG
B_ANAER-POS
B_GRAMN
B_GRAMP
F_FUNGUS
F_YEAST
UNKNOWN
R/data.R
microorganisms.groups.Rd
A tibble with 444 observations and 4 variables:
mo_group ID of the species group / microbiological complex
mo_group
A tibble with 507 observations and 4 variables:
mo ID of the microorganism belonging in the species group / microbiological complex
mo
mo_group_name Name of the species group / microbiological complex, as retrieved with mo_name()
mo_group_name
mo_name()
mo_name Name of the microorganism belonging in the species group / microbiological complex, as retrieved with mo_name()
mo_name
skewness(runif(1000)) -#> [1] 0.07297999 +#> [1] -0.0634746