vignettes/AMR.Rmd
AMR.Rmd
So only 53.7% is suitable for resistance analysis! We can now filter +
So only 53.3% 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 10,739 isolates for analysis. Now our data looks +
So we end up with 10,650 isolates for analysis. Now our data looks like:
head(data_1st)
data_1st %>% freq(genus, species)
Frequency table
Class: character -Length: 10,739 -Available: 10,739 (100%, NA: 0 = 0%) +Length: 10,650 +Available: 10,650 (100%, NA: 0 = 0%) Unique: 4
Shortest: 16 Longest: 24
If you want to get a quick glance of the number of isolates in @@ -1014,50 +1014,50 @@ different bug/drug combinations, you can use the
proportion_SI()
data_1st %>% resistance(AMX) -# [1] 0.5423224
Or can be used in conjunction with group_by() and summarise(), both from the dplyr package:
group_by()
summarise()
@@ -1154,19 +1154,19 @@ own: Hospital A -0.5322120 +0.5346793 Hospital B -0.5366357 +0.5482421 Hospital C -0.5579757 +0.5480192 Hospital D -0.5560205 +0.5347418 @@ -1191,23 +1191,23 @@ all isolates available for every group (i.e. values S, I or R): Hospital A -0.5322120 -3151 +0.5346793 +3071 Hospital B -0.5366357 -3876 +0.5482421 +3783 Hospital C -0.5579757 -1561 +0.5480192 +1666 Hospital D -0.5560205 -2151 +0.5347418 +2130 @@ -1232,27 +1232,27 @@ therapies very easily: Escherichia -0.7761634 -0.8715519 -0.9816804 +0.7705656 +0.8819623 +0.9777207 Klebsiella -0.8148457 -0.9082569 -0.9824854 +0.8226478 +0.9159034 +0.9866778 Staphylococcus -0.8017209 -0.8799102 -0.9816685 +0.7979911 +0.8917411 +0.9769345 Streptococcus -0.5325779 +0.5470616 0.0000000 -0.5325779 +0.5470616 @@ -1280,23 +1280,23 @@ classes, use a antibiotic class selector such as Hospital A -53.2% -26.1% +53.5% +25.9% Hospital B -53.7% -25.5% +54.8% +26.6% Hospital C -55.8% -27.9% +54.8% +26.8% Hospital D -55.6% -26.0% +53.5% +24.8% @@ -1412,16 +1412,18 @@ classes) <mic> and <disk>: mic_values <- random_mic(size = 100) mic_values # Class 'mic' -# [1] 0.0625 0.005 0.005 0.001 256 128 0.125 0.5 0.125 0.025 -# [11] 8 64 0.0625 0.5 0.001 4 0.01 8 0.0625 4 -# [21] 16 8 0.5 0.0625 0.01 0.001 0.01 8 8 0.01 -# [31] 0.5 1 32 8 4 0.5 0.25 32 0.005 8 -# [41] 128 32 0.001 128 8 0.025 64 8 16 0.0625 -# [51] 0.01 0.5 0.025 16 32 256 0.001 16 8 0.01 -# [61] 0.5 8 8 0.0625 0.01 0.125 128 16 0.002 128 -# [71] 64 128 64 32 32 16 64 0.01 64 2 -# [81] 0.25 0.002 0.025 128 0.002 64 0.001 2 32 16 -# [91] 0.005 8 0.25 0.002 16 32 1 0.25 16 0.005
<mic>
<disk>
mic_values <- random_mic(size = 100) mic_values # Class 'mic' -# [1] 0.0625 0.005 0.005 0.001 256 128 0.125 0.5 0.125 0.025 -# [11] 8 64 0.0625 0.5 0.001 4 0.01 8 0.0625 4 -# [21] 16 8 0.5 0.0625 0.01 0.001 0.01 8 8 0.01 -# [31] 0.5 1 32 8 4 0.5 0.25 32 0.005 8 -# [41] 128 32 0.001 128 8 0.025 64 8 16 0.0625 -# [51] 0.01 0.5 0.025 16 32 256 0.001 16 8 0.01 -# [61] 0.5 8 8 0.0625 0.01 0.125 128 16 0.002 128 -# [71] 64 128 64 32 32 16 64 0.01 64 2 -# [81] 0.25 0.002 0.025 128 0.002 64 0.001 2 32 16 -# [91] 0.005 8 0.25 0.002 16 32 1 0.25 16 0.005
# base R: plot(mic_values)
disk_values <- random_disk(size = 100, mo = "E. coli", ab = "cipro") disk_values # Class 'disk' -# [1] 25 31 26 31 24 31 27 17 28 25 21 28 20 20 17 17 26 20 20 29 26 31 30 20 25 -# [26] 25 27 29 29 21 17 27 20 20 17 25 17 20 27 29 19 27 18 28 31 21 23 26 26 27 -# [51] 23 23 21 18 22 23 19 17 22 23 29 28 19 29 20 31 18 25 21 17 18 31 20 21 17 -# [76] 21 28 25 31 24 30 24 17 20 26 31 25 20 30 18 21 29 19 30 20 24 29 23 23 22
# base R: plot(disk_values, mo = "E. coli", ab = "cipro")
head(my_TB_data) # rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin -# 1 S S R R S S -# 2 R R I S I R -# 3 S I S R I S -# 4 I S R R I I -# 5 I I I I I R -# 6 R S R R R S +# 1 S S S I R R +# 2 I S S S R I +# 3 S R R I I R +# 4 I I R I I S +# 5 R I S S R I +# 6 I S S S R R # kanamycin -# 1 I -# 2 R -# 3 I -# 4 R +# 1 R +# 2 I +# 3 S +# 4 S # 5 S -# 6 R
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 -3261 -65.22% -3261 -65.22% +3195 +63.90% +3195 +63.90% 2 Negative -919 -18.38% -4180 -83.60% +1015 +20.30% +4210 +84.20% 3 Multi-drug-resistant -488 -9.76% -4668 -93.36% +437 +8.74% +4647 +92.94% 4 Poly-resistant -235 -4.70% -4903 -98.06% +254 +5.08% +4901 +98.02% 5 Extensively drug-resistant -97 -1.94% +99 +1.98% 5000 100.00% diff --git a/articles/PCA.html b/articles/PCA.html index 6745225c..11bdc2a1 100644 --- a/articles/PCA.html +++ b/articles/PCA.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/articles/SPSS.html b/articles/SPSS.html index 417ce98f..3069920e 100644 --- a/articles/SPSS.html +++ b/articles/SPSS.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 @@ -168,7 +168,7 @@ Dr. Matthijs Berends - 13 November 2022 + 14 November 2022 Source: vignettes/SPSS.Rmd SPSS.Rmd diff --git a/articles/WHONET.html b/articles/WHONET.html index 8065c183..8ec4517e 100644 --- a/articles/WHONET.html +++ b/articles/WHONET.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/articles/datasets.html b/articles/datasets.html index 3a96c9b9..c48d1c29 100644 --- a/articles/datasets.html +++ b/articles/datasets.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 @@ -166,7 +166,7 @@ Data sets for download / own use - 13 November 2022 + 14 November 2022 Source: vignettes/datasets.Rmd datasets.Rmd @@ -1328,13 +1328,13 @@ v3.3 (2021). dosage: Dosage Guidelines from EUCAST -A data set with 169 rows and 9 columns, containing the following +A data set with 336 rows and 9 columns, containing the following column names:ab, name, type, dose, dose_times, administration, notes, original_txt and eucast_version. This data set is in R available as dosage, after you load the AMR package. -It was last updated on 30 October 2022 20:05:46 UTC. Find more info +It was last updated on 14 November 2022 14:20:39 UTC. Find more info about the structure of this data set here. Direct download links: @@ -1342,25 +1342,25 @@ about the structure of this data set tab-separated -text file (15 kB) +text file (29 kB) Download as Microsoft -Excel workbook (14 kB) +Excel workbook (19 kB) Download as Apache -Feather file (11 kB) +Feather file (16 kB) Download as Apache -Parquet file (7 kB) +Parquet file (8 kB) Download as SAS -data file (52 kB) +data file (92 kB) Download as IBM -SPSS Statistics data file (23 kB) +SPSS Statistics data file (43 kB) Download as Stata -DTA file (44 kB) +DTA file (82 kB) Source @@ -1368,7 +1368,8 @@ DTA file (44 kB) EUCAST breakpoints used in this package are based on the dosages in this data set. Currently included dosages in the data set are meant for: ‘EUCAST Clinical -Breakpoint Tables’ v11.0 (2021). +Breakpoint Tables’ v11.0 (2021) and ‘EUCAST Clinical +Breakpoint Tables’ v12.0 (2022). Example content @@ -1406,7 +1407,7 @@ Breakpoint Tables’ v11.0 (2021). iv 25-30 mg/kg x 1 iv -11 +12 AMX @@ -1417,7 +1418,7 @@ Breakpoint Tables’ v11.0 (2021). iv 2 g x 6 iv -11 +12 AMX @@ -1428,7 +1429,7 @@ Breakpoint Tables’ v11.0 (2021). iv 1 g x 3-4 iv -11 +12 AMX @@ -1439,7 +1440,7 @@ Breakpoint Tables’ v11.0 (2021). oral 0.75-1 g x 3 oral -11 +12 AMX @@ -1450,7 +1451,7 @@ Breakpoint Tables’ v11.0 (2021). oral 0.5 g x 3 oral -11 +12 AMX @@ -1461,7 +1462,7 @@ Breakpoint Tables’ v11.0 (2021). oral 0.5 g x 3 oral -11 +12 diff --git a/articles/index.html b/articles/index.html index e38cb3f9..d0fc042d 100644 --- a/articles/index.html +++ b/articles/index.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/articles/resistance_predict.html b/articles/resistance_predict.html index dd314475..f9c3ffa2 100644 --- a/articles/resistance_predict.html +++ b/articles/resistance_predict.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/articles/welcome_to_AMR.html b/articles/welcome_to_AMR.html index 52b2f6c9..d490f986 100644 --- a/articles/welcome_to_AMR.html +++ b/articles/welcome_to_AMR.html @@ -38,7 +38,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/authors.html b/authors.html index 747598f0..263fec0f 100644 --- a/authors.html +++ b/authors.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/index.html b/index.html index 8230d13e..650554a2 100644 --- a/index.html +++ b/index.html @@ -42,7 +42,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/news/index.html b/news/index.html index 94001ee4..7b43f311 100644 --- a/news/index.html +++ b/news/index.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 @@ -132,10 +132,10 @@ -AMR 1.8.2.9050 +AMR 1.8.2.9051 This version will eventually become v2.0! We’re happy to reach a new major milestone soon! -Breaking +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 @@ -151,9 +151,9 @@ Using units in ab_ddd(..., units = "...") had been deprecated and is now not supported anymore. Use ab_ddd_units() instead. -New +New -EUCAST 2022 and CLSI 2022 guidelines have been added for as.rsi(). EUCAST 2022 is now the new default guideline for all MIC and disks diffusion interpretations. +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 at start-up 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 submitted JSS paper (DOI 10.18637/jss.v104.i03). @@ -193,7 +193,7 @@ -Changed +Changed Fix for using as.rsi() on certain EUCAST breakpoints for MIC values Fix for using as.rsi() on NA values (e.g. as.rsi(as.disk(NA), ...)) Fix for using as.rsi() on bug-drug combinations with multiple breakpoints for different body sites @@ -224,7 +224,7 @@ Fix for mo_shortname() in case of higher taxonomic ranks (order, class, phylum) -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 bd5864df..1c7fa741 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -11,7 +11,7 @@ articles: datasets: datasets.html resistance_predict: resistance_predict.html welcome_to_AMR: welcome_to_AMR.html -last_built: 2022-11-13T12:48Z +last_built: 2022-11-14T14:24Z 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 6a56aff5..1bb5bbaf 100644 --- a/reference/AMR-deprecated.html +++ b/reference/AMR-deprecated.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/reference/AMR.html b/reference/AMR.html index 8f21e5a1..43e8b16a 100644 --- a/reference/AMR.html +++ b/reference/AMR.html @@ -62,7 +62,7 @@ Principal component analysis for AMR AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/reference/Rplot005.png b/reference/Rplot005.png index 2df89579..0d4e0ed3 100644 Binary files a/reference/Rplot005.png and b/reference/Rplot005.png differ diff --git a/reference/Rplot006.png b/reference/Rplot006.png index 945aac47..90a68c89 100644 Binary files a/reference/Rplot006.png and b/reference/Rplot006.png differ diff --git a/reference/Rplot007.png b/reference/Rplot007.png index 3ad4cb43..46267b5b 100644 Binary files a/reference/Rplot007.png and b/reference/Rplot007.png differ diff --git a/reference/Rplot008.png b/reference/Rplot008.png index f936024e..8a0d26f2 100644 Binary files a/reference/Rplot008.png and b/reference/Rplot008.png differ diff --git a/reference/Rplot009.png b/reference/Rplot009.png index ccfba30a..7f22c6c7 100644 Binary files a/reference/Rplot009.png and b/reference/Rplot009.png differ diff --git a/reference/WHOCC.html b/reference/WHOCC.html index 79b56105..f54ddb5e 100644 --- a/reference/WHOCC.html +++ b/reference/WHOCC.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/reference/WHONET.html b/reference/WHONET.html index 8a2f8c46..84543124 100644 --- a/reference/WHONET.html +++ b/reference/WHONET.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/reference/ab_from_text.html b/reference/ab_from_text.html index 5d7f7388..9bc1ce78 100644 --- a/reference/ab_from_text.html +++ b/reference/ab_from_text.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/reference/ab_property.html b/reference/ab_property.html index 2e60e285..98936bb5 100644 --- a/reference/ab_property.html +++ b/reference/ab_property.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/reference/add_custom_antimicrobials.html b/reference/add_custom_antimicrobials.html index 4b0f443f..ab30b19a 100644 --- a/reference/add_custom_antimicrobials.html +++ b/reference/add_custom_antimicrobials.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 diff --git a/reference/age.html b/reference/age.html index ffc21997..f1898c34 100644 --- a/reference/age.html +++ b/reference/age.html @@ -10,7 +10,7 @@ AMR (for R) - 1.8.2.9050 + 1.8.2.9051 @@ -195,16 +195,16 @@ df #> birth_date age age_exact age_at_y2k -#> 1 1978-10-01 44 44.11781 21 -#> 2 1994-04-13 28 28.58630 5 -#> 3 1981-11-26 40 40.96438 18 -#> 4 1980-05-08 42 42.51781 19 -#> 5 1978-06-07 44 44.43562 21 -#> 6 1956-08-24 66 66.22192 43 -#> 7 1958-12-06 63 63.93699 41 -#> 8 1950-03-13 72 72.67123 49 -#> 9 1981-10-06 41 41.10411 18 -#> 10 1991-01-09 31 31.84384 8 +#> 1 1932-11-14 90 90.00000 67 +#> 2 1985-08-22 37 37.23014 14 +#> 3 1974-06-23 48 48.39452 25 +#> 4 1954-12-08 67 67.93425 45 +#> 5 1973-01-26 49 49.80000 26 +#> 6 1940-11-21 81 81.98082 59 +#> 7 1964-04-16 58 58.58082 35 +#> 8 1979-11-15 42 42.99726 20 +#> 9 1955-06-26 67 67.38630 44 +#> 10 1975-11-22 46 46.97808 24
vignettes/SPSS.Rmd
SPSS.Rmd
vignettes/datasets.Rmd
datasets.Rmd
dosage
A data set with 169 rows and 9 columns, containing the following +
A data set with 336 rows and 9 columns, containing the following column names:ab, name, type, dose, dose_times, administration, notes, original_txt and eucast_version.
This data set is in R available as dosage, after you load the AMR package.
AMR
It was last updated on 30 October 2022 20:05:46 UTC. Find more info +
It was last updated on 14 November 2022 14:20:39 UTC. Find more info about the structure of this data set here.
Direct download links:
EUCAST breakpoints used in this package are based on the dosages in this data set.
Currently included dosages in the data set are meant for: ‘EUCAST Clinical -Breakpoint Tables’ v11.0 (2021).
This version will eventually become v2.0! We’re happy to reach a new major milestone soon!
units
ab_ddd(..., units = "...")
ab_ddd_units()
as.rsi()
eucast_rules()
as.mo()
mo_*()
NA
as.rsi(as.disk(NA), ...)
mo_shortname()
styler