From c8c8bb4e3aeecf1dd22fe480734ce8c739e00c07 Mon Sep 17 00:00:00 2001 From: "Matthijs S. Berends" Date: Fri, 21 Aug 2020 11:40:13 +0200 Subject: [PATCH] (v1.3.0.9006) website update --- DESCRIPTION | 4 +- NEWS.md | 4 +- R/ab.R | 1 + R/ab_class_selectors.R | 1 + R/ab_property.R | 1 + R/amr.R | 2 + R/data.R | 11 +- R/eucast_rules.R | 1 + R/mo.R | 1 + R/mo_property.R | 1 + R/rsi.R | 1 + data-raw/antibiotics.dta | Bin 329492 -> 329492 bytes data-raw/antibiotics.sas | Bin 1880064 -> 1880064 bytes data-raw/antibiotics.sav | Bin 1406605 -> 1406605 bytes data-raw/antibiotics.xlsx | Bin 66084 -> 66082 bytes data-raw/antivirals.dta | Bin 68841 -> 68841 bytes data-raw/antivirals.sas | Bin 81920 -> 81920 bytes data-raw/antivirals.sav | Bin 69306 -> 69306 bytes data-raw/antivirals.xlsx | Bin 13936 -> 13934 bytes data-raw/internals.R | 72 +-- data-raw/intrinsic_resistant.dta | Bin 3909333 -> 3909333 bytes data-raw/intrinsic_resistant.sas | Bin 3985408 -> 3985408 bytes data-raw/intrinsic_resistant.sav | Bin 4353410 -> 4353410 bytes data-raw/intrinsic_resistant.xlsx | Bin 524510 -> 524509 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14 +- docs/reference/as.ab.html | 14 +- docs/reference/as.disk.html | 9 +- docs/reference/as.mic.html | 9 +- docs/reference/as.mo.html | 14 +- docs/reference/as.rsi.html | 7 +- docs/reference/atc_online.html | 9 +- docs/reference/availability.html | 9 +- docs/reference/bug_drug_combinations.html | 9 +- docs/reference/catalogue_of_life.html | 9 +- docs/reference/catalogue_of_life_version.html | 9 +- docs/reference/count.html | 11 +- docs/reference/eucast_rules.html | 14 +- docs/reference/example_isolates.html | 14 +- docs/reference/example_isolates_unclean.html | 14 +- docs/reference/filter_ab_class.html | 9 +- docs/reference/first_isolate.html | 9 +- docs/reference/g.test.html | 9 +- docs/reference/ggplot_pca.html | 9 +- docs/reference/ggplot_rsi.html | 9 +- docs/reference/guess_ab_col.html | 9 +- docs/reference/index.html | 2 +- docs/reference/intrinsic_resistant.html | 9 +- docs/reference/join.html | 9 +- docs/reference/key_antibiotics.html | 9 +- docs/reference/kurtosis.html | 9 +- docs/reference/lifecycle.html | 9 +- docs/reference/like.html | 9 +- docs/reference/mdro.html | 9 +- docs/reference/microorganisms.codes.html | 14 +- docs/reference/microorganisms.html | 14 +- docs/reference/microorganisms.old.html | 14 +- docs/reference/mo_property.html | 14 +- docs/reference/mo_source.html | 9 +- docs/reference/p_symbol.html | 9 +- docs/reference/pca.html | 9 +- docs/reference/proportion.html | 9 +- docs/reference/resistance_predict.html | 9 +- docs/reference/rsi_translation.html | 7 +- docs/reference/skewness.html | 9 +- docs/reference/translate.html | 9 +- docs/survey.html | 2 +- man/AMR.Rd | 5 + man/WHONET.Rd | 5 + man/ab_property.Rd | 5 + man/antibiotic_class_selectors.Rd | 5 + man/antibiotics.Rd | 5 + man/as.ab.Rd | 5 + man/as.mo.Rd | 5 + man/as.rsi.Rd | 5 + man/eucast_rules.Rd | 5 + man/example_isolates.Rd | 5 + man/example_isolates_unclean.Rd | 5 + man/intrinsic_resistant.Rd | 5 + man/microorganisms.Rd | 5 + man/microorganisms.codes.Rd | 5 + man/microorganisms.old.Rd | 5 + man/mo_property.Rd | 5 + man/rsi_translation.Rd | 5 + vignettes/datasets.Rmd | 12 +- 127 files changed, 982 insertions(+), 470 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 029c4b853..58fe84c04 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: AMR -Version: 1.3.0.9005 -Date: 2020-08-17 +Version: 1.3.0.9006 +Date: 2020-08-21 Title: Antimicrobial Resistance Analysis Authors@R: c( person(role = c("aut", "cre"), diff --git a/NEWS.md b/NEWS.md index 52d745004..c415c0ef8 100755 --- a/NEWS.md +++ b/NEWS.md @@ -1,5 +1,5 @@ -# AMR 1.3.0.9005 -## Last updated: 17 August 2020 +# AMR 1.3.0.9006 +## Last updated: 21 August 2020 ### New * Data set `intrinsic_resistant`. This data set contains all bug-drug combinations where the 'bug' is intrinsic resistant to the 'drug' according to the latest EUCAST insights. It contains just two columns: `microorganism` and `antibiotic`. diff --git a/R/ab.R b/R/ab.R index 3f651de82..4a926ed76 100755 --- a/R/ab.R +++ b/R/ab.R @@ -51,6 +51,7 @@ #' @seealso #' * [antibiotics] for the dataframe that is being used to determine ATCs #' * [ab_from_text()] for a function to retrieve antimicrobial drugs from clinical text (from health care records) +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @export #' @examples diff --git a/R/ab_class_selectors.R b/R/ab_class_selectors.R index bd3592657..0d9b723df 100644 --- a/R/ab_class_selectors.R +++ b/R/ab_class_selectors.R @@ -30,6 +30,7 @@ #' @seealso [filter_ab_class()] for the `filter()` equivalent. #' @name antibiotic_class_selectors #' @export +#' @inheritSection AMR Read more on our website! #' @examples #' \dontrun{ #' library(dplyr) diff --git a/R/ab_property.R b/R/ab_property.R index 0b262f2cd..fd09b1959 100644 --- a/R/ab_property.R +++ b/R/ab_property.R @@ -44,6 +44,7 @@ #' - A [`character`] in all other cases #' @export #' @seealso [antibiotics] +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples #' # all properties: diff --git a/R/amr.R b/R/amr.R index 9a212237c..aa0ff9dfb 100644 --- a/R/amr.R +++ b/R/amr.R @@ -47,6 +47,8 @@ #' - 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 #' +#' @section Reference data publicly available: +#' All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find [all download links on our website](https://msberends.github.io/AMR/articles/datasets.html), which is automatically updated with every code change. #' @section Read more on our website!: #' On our website you can find [a comprehensive tutorial](https://msberends.github.io/AMR/articles/AMR.html) about how to conduct AMR analysis, the [complete documentation of all functions](https://msberends.github.io/AMR/reference) (which reads a lot easier than here in R) and [an example analysis using WHONET data](https://msberends.github.io/AMR/articles/WHONET.html). As we would like to better understand the backgrounds and needs of our users, please [participate in our survey](https://msberends.github.io/AMR/survey.html)! #' @section Contact Us: diff --git a/R/data.R b/R/data.R index 8d06987c2..0eda68d65 100755 --- a/R/data.R +++ b/R/data.R @@ -68,6 +68,7 @@ #' WHONET 2019 software: #' #' European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: +#' @inheritSection AMR Reference data publicly available #' @inheritSection WHOCC WHOCC #' @inheritSection AMR Read more on our website! #' @seealso [microorganisms], [intrinsic_resistant] @@ -118,6 +119,7 @@ #' Parte, A.C. (2018). LPSN — List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; doi: 10.1099/ijsem.0.002786 #' #' Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Germany, Prokaryotic Nomenclature Up-to-Date, and (check included version with [catalogue_of_life_version()]). +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @seealso [as.mo()], [mo_property()], [microorganisms.codes], [intrinsic_resistant] "microorganisms" @@ -142,6 +144,7 @@ catalogue_of_life <- list( #' @source Catalogue of Life: Annual Checklist (public online taxonomic database), (check included annual version with [catalogue_of_life_version()]). #' #' Parte, A.C. (2018). LPSN — List of Prokaryotic names with Standing in Nomenclature (bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68, 1825-1829; doi: 10.1099/ijsem.0.002786 +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @seealso [as.mo()] [mo_property()] [microorganisms] "microorganisms.old" @@ -152,6 +155,7 @@ catalogue_of_life <- list( #' @format A [`data.frame`] with `r format(nrow(microorganisms.codes), big.mark = ",")` observations and `r ncol(microorganisms.codes)` variables: #' - `code`\cr Commonly used code of a microorganism #' - `mo`\cr ID of the microorganism in the [microorganisms] data set +#' @inheritSection AMR Reference data publicly available #' @inheritSection catalogue_of_life Catalogue of Life #' @inheritSection AMR Read more on our website! #' @seealso [as.mo()] [microorganisms] @@ -171,6 +175,7 @@ catalogue_of_life <- list( #' - `patient_id`\cr ID of the patient #' - `mo`\cr ID of microorganism created with [as.mo()], see also [microorganisms] #' - `PEN:RIF`\cr `r sum(sapply(example_isolates, is.rsi))` different antibiotics with class [`rsi`] (see [as.rsi()]); these column names occur in the [antibiotics] data set and can be translated with [ab_name()] +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! "example_isolates" @@ -183,6 +188,7 @@ catalogue_of_life <- list( #' - `hospital`\cr ID of the hospital, from A to C #' - `bacteria`\cr info about microorganism that can be transformed with [as.mo()], see also [microorganisms] #' - `AMX:GEN`\cr 4 different antibiotics that have to be transformed with [as.rsi()] +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! "example_isolates_unclean" @@ -216,6 +222,7 @@ catalogue_of_life <- list( #' - `Comment`\cr Other comments #' - `Date of data entry`\cr Date this data was entered in WHONET #' - `AMP_ND10:CIP_EE`\cr `r sum(sapply(WHONET, is.rsi))` different antibiotics. You can lookup the abbreviations in the [antibiotics] data set, or use e.g. [`ab_name("AMP")`][ab_name()] to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using [as.rsi()]. +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! "WHONET" @@ -234,8 +241,7 @@ catalogue_of_life <- list( #' - `breakpoint_R`\cr Highest MIC value or lowest number of millimetres that leads to "R" #' - `uti`\cr A logical value (`TRUE`/`FALSE`) to indicate whether the rule applies to a urinary tract infection (UTI) #' @details The repository of this `AMR` package contains a file comprising this exact data set: . This file **allows for machine reading EUCAST and CLSI guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically. -#' -#' +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @seealso [intrinsic_resistant] "rsi_translation" @@ -249,6 +255,7 @@ catalogue_of_life <- list( #' @details The repository of this `AMR` package contains a file comprising this exact data set: . This file **allows for machine reading EUCAST guidelines about intrinsic resistance**, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically. #' #' This data set is based on 'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes', version `r EUCAST_VERSION_EXPERT_RULES`. +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples #' if (require("dplyr")) { diff --git a/R/eucast_rules.R b/R/eucast_rules.R index 2f0bbdfd3..08adceef7 100755 --- a/R/eucast_rules.R +++ b/R/eucast_rules.R @@ -150,6 +150,7 @@ EUCAST_VERSION_EXPERT_RULES <- "3.1, 2016" #' #' - EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 9.0, 2019. \cr #' +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples #' \donttest{ diff --git a/R/mo.R b/R/mo.R index 064a10fda..e8e373610 100755 --- a/R/mo.R +++ b/R/mo.R @@ -110,6 +110,7 @@ #' @seealso [microorganisms] for the [`data.frame`] that is being used to determine ID's. #' #' The [mo_property()] functions (like [mo_genus()], [mo_gramstain()]) to get properties based on the returned code. +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples #' \donttest{ diff --git a/R/mo_property.R b/R/mo_property.R index 5836cf4f7..5b079e595 100755 --- a/R/mo_property.R +++ b/R/mo_property.R @@ -54,6 +54,7 @@ #' - A [`character`] in all other cases #' @export #' @seealso [microorganisms] +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples #' # taxonomic tree ----------------------------------------------------------- diff --git a/R/rsi.R b/R/rsi.R index 836b7ffd5..f8bf46f76 100755 --- a/R/rsi.R +++ b/R/rsi.R @@ -90,6 +90,7 @@ #' @aliases rsi #' @export #' @seealso [as.mic()], [as.disk()], [as.mo()] +#' @inheritSection AMR Reference data publicly available #' @inheritSection AMR Read more on our website! #' @examples #' summary(example_isolates) # see all R/SI results at a glance diff --git a/data-raw/antibiotics.dta b/data-raw/antibiotics.dta index 8746329e3513e0c2476cb21f44987c8f96e29573..21cd1dc291afa1d8f71056ae0c2dbce7b6a0df5a 100644 GIT binary patch delta 45 zcmbQzCo-i^WI~0Yk)eWPX}W@ufsuiNp`n$rNn>YgCu3_TQ)?%4YbVRrPS$QV07m@| AO#lD@ delta 45 zcmbQzCo-i^WI~0Yp}B%%X}W@ufsuiNk)f5LMPp}cCu3_TQ)?%4YbVRrPS$QV07vN# ARR910 diff --git a/data-raw/antibiotics.sas b/data-raw/antibiotics.sas index 6742acccb9c11692be9fb8f6e63efd2540a900a6..87263432bf974da46fa0d8fdf34eba8d451fa6d2 100644 GIT binary patch delta 109 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mo_name(mo)) -saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2) -write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE) -haven::write_sas(rsi, "data-raw/rsi_translation.sas") -haven::write_sav(rsi, "data-raw/rsi_translation.sav") -haven::write_dta(rsi, "data-raw/rsi_translation.dta") -openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx") +try(saveRDS(rsi, "data-raw/rsi_translation.rds", version = 2), silent = TRUE) +try(write.table(rsi, "data-raw/rsi_translation.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE) +try(haven::write_sas(rsi, "data-raw/rsi_translation.sas"), silent = TRUE) +try(haven::write_sav(rsi, "data-raw/rsi_translation.sav"), silent = TRUE) +try(haven::write_dta(rsi, "data-raw/rsi_translation.dta"), silent = TRUE) +try(openxlsx::write.xlsx(rsi, "data-raw/rsi_translation.xlsx"), silent = TRUE) mo <- dplyr::mutate_if(microorganisms, ~!is.numeric(.), as.character) -saveRDS(mo, "data-raw/microorganisms.rds", version = 2) -write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE) -haven::write_sas(mo, "data-raw/microorganisms.sas") -haven::write_sav(mo, "data-raw/microorganisms.sav") -haven::write_dta(mo, "data-raw/microorganisms.dta") -openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx") +try(saveRDS(mo, "data-raw/microorganisms.rds", version = 2), silent = TRUE) +try(write.table(mo, "data-raw/microorganisms.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE) +try(haven::write_sas(mo, "data-raw/microorganisms.sas"), silent = TRUE) +try(haven::write_sav(mo, "data-raw/microorganisms.sav"), silent = TRUE) +try(haven::write_dta(mo, "data-raw/microorganisms.dta"), silent = TRUE) +try(openxlsx::write.xlsx(mo, "data-raw/microorganisms.xlsx"), silent = TRUE) -saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2) -write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE) -haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas") -haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav") -haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta") -openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx") +try(saveRDS(microorganisms.old, "data-raw/microorganisms.old.rds", version = 2), silent = TRUE) +try(write.table(microorganisms.old, "data-raw/microorganisms.old.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE) +try(haven::write_sas(microorganisms.old, "data-raw/microorganisms.old.sas"), silent = TRUE) +try(haven::write_sav(microorganisms.old, "data-raw/microorganisms.old.sav"), silent = TRUE) +try(haven::write_dta(microorganisms.old, "data-raw/microorganisms.old.dta"), silent = TRUE) +try(openxlsx::write.xlsx(microorganisms.old, "data-raw/microorganisms.old.xlsx"), silent = TRUE) ab <- dplyr::mutate_if(antibiotics, ~!is.numeric(.), as.character) -saveRDS(ab, "data-raw/antibiotics.rds", version = 2) -write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE) -haven::write_sas(ab, "data-raw/antibiotics.sas") -haven::write_sav(ab, "data-raw/antibiotics.sav") -haven::write_dta(ab, "data-raw/antibiotics.dta") -openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx") +try(saveRDS(ab, "data-raw/antibiotics.rds", version = 2), silent = TRUE) +try(write.table(ab, "data-raw/antibiotics.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE) +try(haven::write_sas(ab, "data-raw/antibiotics.sas"), silent = TRUE) +try(haven::write_sav(ab, "data-raw/antibiotics.sav"), silent = TRUE) +try(haven::write_dta(ab, "data-raw/antibiotics.dta"), silent = TRUE) +try(openxlsx::write.xlsx(ab, "data-raw/antibiotics.xlsx"), silent = TRUE) av <- dplyr::mutate_if(antivirals, ~!is.numeric(.), as.character) -saveRDS(av, "data-raw/antivirals.rds", version = 2) -write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE) -haven::write_sas(av, "data-raw/antivirals.sas") -haven::write_sav(av, "data-raw/antivirals.sav") -haven::write_dta(av, "data-raw/antivirals.dta") -openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx") +try(saveRDS(av, "data-raw/antivirals.rds", version = 2), silent = TRUE) +try(write.table(av, "data-raw/antivirals.txt", sep = "\t", na = "", row.names = FALSE), silent = TRUE) +try(haven::write_sas(av, "data-raw/antivirals.sas"), silent = TRUE) +try(haven::write_sav(av, "data-raw/antivirals.sav"), silent = TRUE) +try(haven::write_dta(av, "data-raw/antivirals.dta"), silent = TRUE) +try(openxlsx::write.xlsx(av, "data-raw/antivirals.xlsx"), silent = TRUE) -saveRDS(intrinsic_resistant, "data-raw/intrinsic_resistant.rds", version = 2) -write.table(intrinsic_resistant, "data-raw/intrinsic_resistant.txt", sep = "\t", na = "", row.names = FALSE) -haven::write_sas(intrinsic_resistant, "data-raw/intrinsic_resistant.sas") -haven::write_sav(intrinsic_resistant, "data-raw/intrinsic_resistant.sav") 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1.3.0.9005 + 1.3.0.9006 diff --git a/docs/articles/AMR.html b/docs/articles/AMR.html index a10091459..ff9e9ef89 100644 --- a/docs/articles/AMR.html +++ b/docs/articles/AMR.html @@ -39,7 +39,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -75,6 +75,13 @@ Predict antimicrobial resistance +
  • + + + + Download our reference data sets for own use + +
  • @@ -186,7 +193,7 @@

    How to conduct AMR analysis

    Matthijs S. Berends

    -

    14 August 2020

    +

    21 August 2020

    Source:     vignettes/AMR.Rmd @@ -195,7 +202,7 @@ -

    Note: values on this page will change with every website update since they are based on randomly created values and the page was written in R Markdown. However, the methodology remains unchanged. This page was generated on 14 August 2020.

    +

    Note: values on this page will change with every website update since they are based on randomly created values and the page was written in R Markdown. However, the methodology remains unchanged. This page was generated on 21 August 2020.

    Introduction

    @@ -226,21 +233,21 @@ -2020-08-14 +2020-08-21 abcd Escherichia coli S S -2020-08-14 +2020-08-21 abcd Escherichia coli S R -2020-08-14 +2020-08-21 efgh Escherichia coli R @@ -354,71 +361,71 @@ -2010-03-16 +2011-03-20 +W2 +Hospital A +Streptococcus pneumoniae +S +S +S +R +F + + +2011-12-03 X9 Hospital B -Staphylococcus aureus +Klebsiella pneumoniae R -S +I S S F - -2013-10-27 -G3 -Hospital A + +2012-11-11 +A5 +Hospital D Staphylococcus aureus S -S R S +S M - -2014-12-09 -F7 + +2012-09-03 +Y3 Hospital C Escherichia coli R S -S -S -M - - -2014-06-08 -S9 -Hospital B -Klebsiella pneumoniae -S -S -S -S +R +R F -2015-01-01 -N10 -Hospital A -Streptococcus pneumoniae +2012-11-19 +I3 +Hospital C +Escherichia coli +S +S +S R +M + + +2015-06-05 +Q7 +Hospital B +Escherichia coli +S S S S F - -2015-11-12 -H6 -Hospital B -Staphylococcus aureus -S -S -S -S -M -

    Now, let’s start the cleaning and the analysis!

    @@ -452,16 +459,16 @@ Longest: 1

    1 M -10,276 -51.38% -10,276 -51.38% +10,358 +51.79% +10,358 +51.79% 2 F -9,724 -48.62% +9,642 +48.21% 20,000 100.00% @@ -511,7 +518,7 @@ Longest: 1

    # NOTE: Using column `date` as input for `col_date`. # NOTE: Using column `patient_id` as input for `col_patient_id`.
    -

    So only 28.4% is suitable for resistance analysis! We can now filter on it with the filter() function, also from the dplyr package:

    +

    So only 28.3% is suitable for resistance analysis! We can now filter on it with the filter() function, also from the dplyr package:

     data_1st <- data %>% 
   filter(first == TRUE)
@@ -525,7 +532,7 @@ Longest: 1
    
 
    
 
    
 First weighted isolates
    
-
    We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient N8, sorted on date:
    
+
    We made a slight twist to the CLSI algorithm, to take into account the antimicrobial susceptibility profile. Have a look at all isolates of patient C8, sorted on date:
    
 
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 isolate
 
    
 
    
 12010-05-17N82010-01-13C8
 B_ESCHR_COLIRS
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 22010-07-03N82010-02-19C8
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 32010-07-31N82010-03-12C8
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 42010-09-13N82010-03-25C8
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 52010-09-15N82010-04-28C8
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 62010-10-16N82010-07-22C8
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 72010-10-17N82010-12-05C8
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 82010-10-24N82011-01-18C8
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 92010-12-27N82011-05-24C8
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 102011-02-25N82011-06-24C8
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 S
 
    
     
 
    
-
    Only 1 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The key_antibiotics() function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.
    
+
    Only 2 isolates are marked as ‘first’ according to CLSI guideline. But when reviewing the antibiogram, it is obvious that some isolates are absolutely different strains and should be included too. This is why we weigh isolates, based on their antibiogram. The key_antibiotics() function adds a vector with 18 key antibiotics: 6 broad spectrum ones, 6 small spectrum for Gram negatives and 6 small spectrum for Gram positives. These can be defined by the user.
    
 
    If a column exists with a name like ‘key(…)ab’ the first_isolate() function will automatically use it and determine the first weighted isolates. Mind the NOTEs in below output:
    
 
     data <- data %>% 
@@ -679,10 +686,10 @@ Longest: 1
    
 
 
 1
-2010-05-17
-N8
+2010-01-13
+C8
 B_ESCHR_COLI
-R
+S
 S
 S
 S
@@ -691,59 +698,59 @@ Longest: 1
    
 
 
 2
-2010-07-03
-N8
+2010-02-19
+C8
 B_ESCHR_COLI
 S
 S
 S
 S
 FALSE
-TRUE
+FALSE
 
 
 3
-2010-07-31
-N8
+2010-03-12
+C8
 B_ESCHR_COLI
 R
-R
-R
-R
+S
+S
+S
 FALSE
 TRUE
 
 
 4
-2010-09-13
-N8
+2010-03-25
+C8
 B_ESCHR_COLI
 S
 S
 R
-S
+R
 FALSE
 TRUE
 
 
 5
-2010-09-15
-N8
+2010-04-28
+C8
 B_ESCHR_COLI
-I
-S
+R
 S
+R
 S
 FALSE
 TRUE
 
 
 6
-2010-10-16
-N8
+2010-07-22
+C8
 B_ESCHR_COLI
-R
-R
+S
+S
 S
 S
 FALSE
@@ -751,61 +758,61 @@ Longest: 1
    
 
 
 7
-2010-10-17
-N8
+2010-12-05
+C8
 B_ESCHR_COLI
 S
 S
 S
 S
 FALSE
-TRUE
+FALSE
 
 
 8
-2010-10-24
-N8
+2011-01-18
+C8
 B_ESCHR_COLI
 R
+R
 S
 S
-S
-FALSE
+TRUE
 TRUE
 
 
 9
-2010-12-27
-N8
+2011-05-24
+C8
 B_ESCHR_COLI
-S
-S
-S
+R
+I
+R
 S
 FALSE
 TRUE
 
 
 10
-2011-02-25
-N8
+2011-06-24
+C8
 B_ESCHR_COLI
 S
 S
 S
 S
 FALSE
-FALSE
+TRUE
 
 
 
-
    Instead of 1, now 9 isolates are flagged. In total, 78.0% of all isolates are marked ‘first weighted’ - 49.7% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.
    
+
    Instead of 2, now 8 isolates are flagged. In total, 78.4% of all isolates are marked ‘first weighted’ - 50.1% more than when using the CLSI guideline. In real life, this novel algorithm will yield 5-10% more isolates than the classic CLSI guideline.
    
 
    As with filter_first_isolate(), there’s a shortcut for this new algorithm too:
    
 
     data_1st <- data %>% 
   filter_first_weighted_isolate()
 
    
-
    So we end up with 15,607 isolates for analysis.
    
+
    So we end up with 15,686 isolates for analysis.
    
 
    We can remove unneeded columns:
    
 
     data_1st <- data_1st %>% 
@@ -851,76 +858,12 @@ Longest: 1
    
 
 
 1
-2010-03-16
-X9
-Hospital B
-B_STPHY_AURS
-R
-S
-S
-S
-F
-Gram-positive
-Staphylococcus
-aureus
-TRUE
-
-
-2
-2013-10-27
-G3
-Hospital A
-B_STPHY_AURS
-S
-S
-R
-S
-M
-Gram-positive
-Staphylococcus
-aureus
-TRUE
-
-
-3
-2014-12-09
-F7
-Hospital C
-B_ESCHR_COLI
-R
-S
-S
-S
-M
-Gram-negative
-Escherichia
-coli
-TRUE
-
-
-4
-2014-06-08
-S9
-Hospital B
-B_KLBSL_PNMN
-R
-S
-S
-S
-F
-Gram-negative
-Klebsiella
-pneumoniae
-TRUE
-
-
-5
-2015-01-01
-N10
+2011-03-20
+W2
 Hospital A
 B_STRPT_PNMN
-R
-R
+S
+S
 S
 R
 F
@@ -930,21 +873,85 @@ Longest: 1
    
 TRUE
 
 
-7
-2014-08-04
-O9
+3
+2012-11-11
+A5
 Hospital D
 B_STPHY_AURS
 R
-I
 R
 S
-F
+S
+M
 Gram-positive
 Staphylococcus
 aureus
 TRUE
 
+
+4
+2012-09-03
+Y3
+Hospital C
+B_ESCHR_COLI
+R
+S
+R
+R
+F
+Gram-negative
+Escherichia
+coli
+TRUE
+
+
+5
+2012-11-19
+I3
+Hospital C
+B_ESCHR_COLI
+S
+S
+S
+R
+M
+Gram-negative
+Escherichia
+coli
+TRUE
+
+
+8
+2013-11-06
+B1
+Hospital B
+B_KLBSL_PNMN
+R
+S
+S
+S
+M
+Gram-negative
+Klebsiella
+pneumoniae
+TRUE
+
+
+9
+2017-01-21
+U3
+Hospital D
+B_KLBSL_PNMN
+R
+S
+S
+S
+F
+Gram-negative
+Klebsiella
+pneumoniae
+TRUE
+
 
 
 
    Time for the analysis!
    
@@ -968,8 +975,8 @@ Longest: 1
    
 
    
 
    Frequency table
    
 
    Class: character
    
-Length: 15,607
    
-Available: 15,607 (100%, NA: 0 = 0%)
    
+Length: 15,686
    
+Available: 15,686 (100%, NA: 0 = 0%)
    
 Unique: 4
    
 
    Shortest: 16
    
 Longest: 24
    
@@ -986,33 +993,33 @@ Longest: 24
    
 
 1
 Escherichia coli
-7,836
-50.21%
-7,836
-50.21%
+7,774
+49.56%
+7,774
+49.56%
 
 
 2
 Staphylococcus aureus
-3,899
-24.98%
-11,735
-75.19%
+3,952
+25.19%
+11,726
+74.75%
 
 
 3
 Streptococcus pneumoniae
-2,337
-14.97%
-14,072
-90.16%
+2,367
+15.09%
+14,093
+89.84%
 
 
 4
 Klebsiella pneumoniae
-1,535
-9.84%
-15,607
+1,593
+10.16%
+15,686
 100.00%
 
 
@@ -1041,50 +1048,50 @@ Longest: 24
    
 
 E. coli
 AMX
-3854
-265
-3717
-7836
+3685
+257
+3832
+7774
 
 
 E. coli
 AMC
-6244
-287
-1305
-7836
+6104
+275
+1395
+7774
 
 
 E. coli
 CIP
-5880
+5979
 0
-1956
-7836
+1795
+7774
 
 
 E. coli
 GEN
-7050
+6986
 0
-786
-7836
+788
+7774
 
 
 K. pneumoniae
 AMX
 0
 0
-1535
-1535
+1593
+1593
 
 
 K. pneumoniae
 AMC
-1199
-50
-286
-1535
+1269
+57
+267
+1593
 
 
 
@@ -1109,34 +1116,34 @@ Longest: 24
    
 
 E. coli
 CIP
-5880
+5979
 0
-1956
-7836
+1795
+7774
 
 
 K. pneumoniae
 CIP
-1166
+1213
 0
-369
-1535
+380
+1593
 
 
 S. aureus
 CIP
-2942
+3003
 0
-957
-3899
+949
+3952
 
 
 S. pneumoniae
 CIP
-1799
+1820
 0
-538
-2337
+547
+2367
 
 
 
@@ -1149,7 +1156,7 @@ Longest: 24
    
 
    As per the EUCAST guideline of 2019, we calculate resistance as the proportion of R (proportion_R(), equal to resistance()) and susceptibility as the proportion of S and I (proportion_SI(), equal to susceptibility()). These functions can be used on their own:
    
 
     data_1st %>% resistance(AMX)
-# [1] 0.5233549
+# [1] 0.5350631
 
    
 
    Or can be used in conjuction with group_by() and summarise(), both from the dplyr package:
    
 
    @@ -1166,19 +1173,19 @@ Longest: 24
    
 
 
 Hospital A
-0.5238399
+0.5338783
 
 
 Hospital B
-0.5201802
+0.5368875
 
 
 Hospital C
-0.5259455
+0.5367068
 
 
 Hospital D
-0.5264182
+0.5322422
 
 
 
@@ -1199,23 +1206,23 @@ Longest: 24
    
 
 
 Hospital A
-0.5238399
-4698
+0.5338783
+4649
 
 
 Hospital B
-0.5201802
-5550
+0.5368875
+5571
 
 
 Hospital C
-0.5259455
-2274
+0.5367068
+2411
 
 
 Hospital D
-0.5264182
-3085
+0.5322422
+3055
 
 
 
@@ -1238,27 +1245,27 @@ Longest: 24
    
 
 
 Escherichia
-0.8334609
-0.8996937
-0.9857070
+0.8205557
+0.8986365
+0.9855930
 
 
 Klebsiella
-0.8136808
-0.8983713
-0.9798046
+0.8323917
+0.8901444
+0.9855618
 
 
 Staphylococcus
-0.8304694
-0.9253655
-0.9894845
+0.8276822
+0.9210526
+0.9868421
 
 
 Streptococcus
-0.5537013
+0.5504858
 0.0000000
-0.5537013
+0.5504858
 
 
 
diff --git a/docs/articles/AMR_files/figure-html/plot 1-1.png b/docs/articles/AMR_files/figure-html/plot 1-1.png
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diff --git a/docs/articles/EUCAST.html b/docs/articles/EUCAST.html
index 39ad84a92..3ecd97a7a 100644
--- a/docs/articles/EUCAST.html
+++ b/docs/articles/EUCAST.html
@@ -39,7 +39,7 @@
       
       
         AMR (for R)
-        1.3.0.9005
+        1.3.0.9006
       
     
    
 
diff --git a/docs/articles/MDR.html b/docs/articles/MDR.html
index 3db87980a..2f74d5d6f 100644
--- a/docs/articles/MDR.html
+++ b/docs/articles/MDR.html
@@ -39,7 +39,7 @@
       
       
         AMR (for R)
-        1.3.0.9005
+        1.3.0.9006
       
     
    
 
@@ -320,17 +320,17 @@ Unique: 2
    
 
     head(my_TB_data)
 #   rifampicin isoniazid gatifloxacin ethambutol pyrazinamide moxifloxacin
-# 1          S         S            S          S            S            R
-# 2          S         R            S          R            S            S
-# 3          R         S            S          S            I            R
-# 4          R         S            R          S            R            R
-# 5          R         S            S          R            S            R
-# 6          S         R            I          S            R            S
+# 1          I         S            S          S            S            R
+# 2          S         S            S          R            R            I
+# 3          R         S            S          R            S            I
+# 4          R         S            S          R            S            S
+# 5          S         R            I          R            I            R
+# 6          R         R            S          R            R            R
 #   kanamycin
 # 1         S
 # 2         R
 # 3         R
-# 4         S
+# 4         I
 # 5         R
 # 6         R
 
    
@@ -368,40 +368,40 @@ Unique: 5
    
 
 1
 Mono-resistant
-3203
-64.06%
-3203
-64.06%
+3233
+64.66%
+3233
+64.66%
 
 
 2
 Negative
-682
-13.64%
-3885
-77.70%
+698
+13.96%
+3931
+78.62%
 
 
 3
 Multi-drug-resistant
-627
-12.54%
-4512
-90.24%
+556
+11.12%
+4487
+89.74%
 
 
 4
 Poly-resistant
-268
-5.36%
-4780
-95.60%
+300
+6.00%
+4787
+95.74%
 
 
 5
 Extensively drug-resistant
-220
-4.40%
+213
+4.26%
 5000
 100.00%
 
diff --git a/docs/articles/PCA.html b/docs/articles/PCA.html
index 9b7942afd..dc573f075 100644
--- a/docs/articles/PCA.html
+++ b/docs/articles/PCA.html
@@ -39,7 +39,7 @@
       
       
         AMR (for R)
-        1.3.0.9005
+        1.3.0.9006
       
     
    
 
diff --git a/docs/articles/SPSS.html b/docs/articles/SPSS.html
index 5630c12f4..a7fa1ef4f 100644
--- a/docs/articles/SPSS.html
+++ b/docs/articles/SPSS.html
@@ -39,7 +39,7 @@
       
       
         AMR (for R)
-        1.3.0.9005
+        1.3.0.9006
    @@ -193,7 +193,7 @@

    How to import data from SPSS / SAS / Stata

    Matthijs S. Berends

    -

    17 August 2020

    +

    21 August 2020

    Source: vignettes/SPSS.Rmd diff --git a/docs/articles/WHONET.html b/docs/articles/WHONET.html index 574daebba..2bd2a3452 100644 --- a/docs/articles/WHONET.html +++ b/docs/articles/WHONET.html @@ -39,7 +39,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 diff --git a/docs/articles/benchmarks.html b/docs/articles/benchmarks.html index d8f018188..90c3a146a 100644 --- a/docs/articles/benchmarks.html +++ b/docs/articles/benchmarks.html @@ -39,7 +39,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 @@ -229,21 +229,21 @@ times = 10) print(S.aureus, unit = "ms", signif = 2) # Unit: milliseconds -# expr min lq mean median uq max neval -# as.mo("sau") 8.8 10.0 24 12 38 57 10 -# as.mo("stau") 170.0 170.0 180 170 190 210 10 -# as.mo("STAU") 160.0 170.0 180 170 200 220 10 -# as.mo("staaur") 9.6 10.0 13 11 12 36 10 -# as.mo("STAAUR") 10.0 10.0 25 12 34 80 10 -# as.mo("S. aureus") 14.0 15.0 21 15 18 47 10 -# as.mo("S aureus") 12.0 15.0 21 16 18 45 10 -# as.mo("Staphylococcus aureus") 8.9 9.4 15 11 12 37 10 -# as.mo("Staphylococcus aureus (MRSA)") 900.0 920.0 940 940 960 1000 10 -# as.mo("Sthafilokkockus aaureuz") 410.0 420.0 450 450 470 520 10 -# as.mo("MRSA") 8.8 10.0 16 11 12 38 10 -# as.mo("VISA") 13.0 16.0 27 19 41 47 10 -# as.mo("VRSA") 13.0 16.0 22 18 19 42 10 -# as.mo(22242419) 140.0 140.0 150 140 160 170 10 +# expr min lq mean median uq max neval +# as.mo("sau") 8.7 9.3 13 9.8 12 40 10 +# as.mo("stau") 160.0 180.0 200 200.0 210 220 10 +# as.mo("STAU") 160.0 180.0 190 190.0 200 210 10 +# as.mo("staaur") 9.8 12.0 15 12.0 12 42 10 +# as.mo("STAAUR") 8.4 8.7 13 10.0 12 37 10 +# as.mo("S. aureus") 13.0 16.0 38 18.0 45 150 10 +# as.mo("S aureus") 12.0 17.0 21 17.0 18 48 10 +# as.mo("Staphylococcus aureus") 7.1 8.7 12 9.7 11 38 10 +# as.mo("Staphylococcus aureus (MRSA)") 880.0 920.0 930 930.0 960 980 10 +# as.mo("Sthafilokkockus aaureuz") 400.0 430.0 450 440.0 460 500 10 +# as.mo("MRSA") 8.6 12.0 20 12.0 37 42 10 +# as.mo("VISA") 15.0 17.0 20 18.0 19 40 10 +# as.mo("VRSA") 13.0 14.0 19 17.0 19 46 10 +# as.mo(22242419) 140.0 140.0 160 150.0 170 210 10

    In the table above, all measurements are shown in milliseconds (thousands of seconds). A value of 5 milliseconds means it can determine 200 input values per second. It case of 100 milliseconds, this is only 10 input values per second.

    @@ -278,9 +278,9 @@ print(run_it, unit = "ms", signif = 3) # Unit: milliseconds # expr min lq mean median uq max neval -# mo_name(x) 1810 1850 1980 1940 2130 2230 10 +# mo_name(x) 1750 1790 1830 1810 1850 1950 10 -

    So transforming 500,000 values (!!) of 50 unique values only takes 1.94 seconds. You only lose time on your unique input values.

    +

    So transforming 500,000 values (!!) of 50 unique values only takes 1.81 seconds. You only lose time on your unique input values.

    @@ -293,12 +293,12 @@ times = 10) print(run_it, unit = "ms", signif = 3) # Unit: milliseconds -# expr min lq mean median uq max neval -# A 5.080 5.220 5.81 5.66 6.46 7.16 10 -# B 10.000 10.200 14.40 10.60 11.30 49.00 10 -# C 0.862 0.875 1.04 1.05 1.14 1.40 10 +# expr min lq mean median uq max neval +# A 6.08 6.23 10.40 6.56 7.03 44.90 10 +# B 11.70 12.00 12.70 12.70 13.60 13.90 10 +# C 1.05 1.11 1.19 1.13 1.25 1.55 10

    -

    So going from mo_name("Staphylococcus aureus") to "Staphylococcus aureus" takes 0.001 seconds - it doesn’t even start calculating if the result would be the same as the expected resulting value. That goes for all helper functions:

    +

    So going from mo_name("Staphylococcus aureus") to "Staphylococcus aureus" takes 0.0011 seconds - it doesn’t even start calculating if the result would be the same as the expected resulting value. That goes for all helper functions:

     run_it <- microbenchmark(A = mo_species("aureus"),
                          B = mo_genus("Staphylococcus"),
@@ -311,15 +311,15 @@
                          times = 10)
 print(run_it, unit = "ms", signif = 3)
 # Unit: milliseconds
-#  expr   min    lq  mean median    uq  max neval
-#     A 0.869 0.889 0.951  0.904 1.010 1.19    10
-#     B 0.837 0.873 0.977  0.937 1.010 1.36    10
-#     C 0.869 0.874 1.020  0.921 1.130 1.40    10
-#     D 0.829 0.858 0.898  0.862 0.873 1.21    10
-#     E 0.862 0.870 0.983  0.918 1.050 1.36    10
-#     F 0.841 0.850 0.915  0.867 0.907 1.24    10
-#     G 0.842 0.851 0.940  0.898 1.000 1.16    10
-#     H 0.854 0.864 1.030  0.920 1.170 1.60    10
+#  expr   min    lq  mean median   uq  max neval
+#     A 0.886 1.010 1.040  1.020 1.06 1.25    10
+#     B 1.010 1.030 1.150  1.040 1.27 1.64    10
+#     C 0.885 1.030 1.110  1.060 1.26 1.29    10
+#     D 0.812 0.822 1.000  1.000 1.05 1.43    10
+#     E 0.827 0.989 1.070  1.030 1.23 1.35    10
+#     F 0.887 0.994 1.070  1.040 1.08 1.35    10
+#     G 0.812 0.839 0.969  0.916 1.04 1.32    10
+#     H 0.815 1.020 1.090  1.050 1.30 1.37    10

    Of course, when running mo_phylum("Firmicutes") the function has zero knowledge about the actual microorganism, namely S. aureus. But since the result would be "Firmicutes" anyway, there is no point in calculating the result. And because this package ‘knows’ all phyla of all known bacteria (according to the Catalogue of Life), it can just return the initial value immediately.

    @@ -347,14 +347,14 @@ times = 100) print(run_it, unit = "ms", signif = 4) # Unit: milliseconds -# expr min lq mean median uq max neval -# en 10.72 11.54 15.34 12.76 13.82 44.53 100 -# de 11.47 12.77 17.24 13.60 14.78 55.48 100 -# nl 14.58 15.91 19.06 16.96 18.46 46.24 100 -# es 11.24 11.96 16.86 13.17 14.70 50.05 100 -# it 11.35 12.42 17.79 13.52 16.28 50.31 100 -# fr 11.41 12.29 17.08 13.43 15.44 53.91 100 -# pt 11.34 12.06 16.23 13.25 14.80 51.96 100 +# expr min lq mean median uq max neval +# en 12.88 13.52 16.72 14.63 16.00 55.03 100 +# de 13.79 14.51 18.36 15.11 16.67 136.90 100 +# nl 17.72 18.59 22.30 20.15 21.87 54.69 100 +# es 13.78 14.38 19.16 15.35 16.86 49.96 100 +# it 13.83 14.40 18.57 15.24 16.32 58.12 100 +# fr 13.72 14.47 19.67 15.21 17.46 52.22 100 +# pt 13.73 14.43 17.76 15.10 16.85 51.69 100

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z(!b?vw>+9M@Biof{(X`a3aE}N5?plrPk#G%bppKc6okUp1`6chVfgy*gCz9R)X-ww zJMDDxe=WxEk0wgMA4gJ074iQG@qPz-zh7I~$$08lY9wbb{QF}5eqR&_u1b(y*h%ld jx9;}}eE9!X%yXZ-fNdqv#eBKz2>4T0R9DElVdnKe?bS)m diff --git a/docs/articles/datasets.html b/docs/articles/datasets.html index 93142c345..6535e2e92 100644 --- a/docs/articles/datasets.html +++ b/docs/articles/datasets.html @@ -39,7 +39,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 @@ -200,15 +200,14 @@ -

    This package contains a lot of reference data sets that are all reliable, up-to-date and free to download. You can even use them outside of R, for example to teach your laboratory information system (LIS) about intrinsic resistance!

    -

    We included them in our AMR package, but also automatically ‘mirror’ them to our public repository in different software formats. On this page, we explain how to download them and how the structure of the data sets look like. The tab separated files allow for machine reading taxonomic data and EUCAST and CLSI interpretation guidelines, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. We also offer all data sets in formats for R, SPSS, SAS, Stata and Excel.

    -

    Note: Years and dates of updates mentioned on this page, are from on AMR package version 1.3.0.9005, online released on 17 August 2020. If you are reading this page from within R, please visit our website for the latest update.

    +

    All reference data (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are reliable, up-to-date and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply tab separated files that are machine-readable and suitable for input in any software program, such as laboratory information systems.

    +

    On this page, we explain how to download them and how the structure of the data sets look like. If you are reading this page from within R, please visit our website, which is automatically updated with every code change.

    Microorganisms (currently accepted names)

    This data set is in R available as microorganisms, after you load the AMR package.

    It was last updated on 28 July 2020 20:52:40 CEST.

    -

    Direct download links:
    R file (.rds), 2.7 MB – Excel workbook (.xlsx), 6.1 MB – SPSS file (.sav), 28.2 MB – Stata file (.dta), 28.2 MB – SAS file (.sas), 25.2 MB – Tab separated file (.txt), 13.3 MB.

    +

    Direct download links:
    R file (.rds), 2.7 MB – Excel workbook (.xlsx), 6.1 MB – SPSS file (.sav), 28.2 MB – Stata file (.dta), 25.2 MB – SAS file (.sas), 26.2 MB – tab separated file (.txt), 13.3 MB.

    Source

    @@ -413,7 +412,7 @@ Microorganisms (previously accepted names)

    This data set is in R available as microorganisms.old, after you load the AMR package.

    It was last updated on 28 May 2020 11:17:56 CEST.

    -

    Direct download links:
    R file (.rds), 0.3 MB – Excel workbook (.xlsx), 0.4 MB – SPSS file (.sav), 1.9 MB – Stata file (.dta), 1.9 MB – SAS file (.sas), 1.8 MB – Tab separated file (.txt), 0.8 MB.

    +

    Direct download links:
    R file (.rds), 0.3 MB – Excel workbook (.xlsx), 0.4 MB – SPSS file (.sav), 1.9 MB – Stata file (.dta), 1.8 MB – SAS file (.sas), 1.9 MB – tab separated file (.txt), 0.8 MB.

    Source

    @@ -466,7 +465,7 @@ Antibiotic agents

    This data set is in R available as antibiotics, after you load the AMR package.

    It was last updated on 31 July 2020 12:12:13 CEST.

    -

    Direct download links:
    R file (.rds), 37 kB – Excel workbook (.xlsx), 65 kB – SPSS file (.sav), 1.3 MB – Stata file (.dta), 1.3 MB – SAS file (.sas), 0.3 MB – Tab separated file (.txt), 0.1 MB.

    +

    Direct download links:
    R file (.rds), 37 kB – Excel workbook (.xlsx), 65 kB – SPSS file (.sav), 1.3 MB – Stata file (.dta), 0.3 MB – SAS file (.sas), 1.8 MB – tab separated file (.txt), 0.1 MB.

    Source

    @@ -622,7 +621,7 @@ Antiviral agents

    This data set is in R available as antivirals, after you load the AMR package.

    It was last updated on 23 November 2019 19:03:43 CET.

    -

    Direct download links:
    R file (.rds), 5 kB – Excel workbook (.xlsx), 14 kB – SPSS file (.sav), 68 kB – Stata file (.dta), 68 kB – SAS file (.sas), 67 kB – Tab separated file (.txt), 16 kB.

    +

    Direct download links:
    R file (.rds), 5 kB – Excel workbook (.xlsx), 14 kB – SPSS file (.sav), 68 kB – Stata file (.dta), 67 kB – SAS file (.sas), 80 kB – tab separated file (.txt), 16 kB.

    Source

    @@ -737,7 +736,7 @@ Intrinsic bacterial resistance

    This data set is in R available as intrinsic_resistant, after you load the AMR package.

    It was last updated on 14 August 2020 14:18:20 CEST.

    -

    Direct download links:
    R file (.rds), 97 kB – Excel workbook (.xlsx), 0.5 MB – SPSS file (.sav), 4.2 MB – Stata file (.dta), 4.2 MB – SAS file (.sas), 3.7 MB – Tab separated file (.txt), 1.8 MB.

    +

    Direct download links:
    R file (.rds), 97 kB – Excel workbook (.xlsx), 0.5 MB – SPSS file (.sav), 4.2 MB – Stata file (.dta), 3.7 MB – SAS file (.sas), 3.8 MB – tab separated file (.txt), 1.8 MB.

    Source

    @@ -788,7 +787,7 @@ Interpretation from MIC values / disk diameters to R/SI

    This data set is in R available as rsi_translation, after you load the AMR package.

    It was last updated on 29 July 2020 13:12:34 CEST.

    -

    Direct download links:
    R file (.rds), 55 kB – Excel workbook (.xlsx), 0.6 MB – SPSS file (.sav), 3.4 MB – Stata file (.dta), 3.4 MB – SAS file (.sas), 3 MB – Tab separated file (.txt), 1.5 MB.

    +

    Direct download links:
    R file (.rds), 55 kB – Excel workbook (.xlsx), 0.6 MB – SPSS file (.sav), 3.4 MB – Stata file (.dta), 3 MB – SAS file (.sas), 3.2 MB – tab separated file (.txt), 1.5 MB.

    Source

    diff --git a/docs/articles/index.html b/docs/articles/index.html index 62169eb1e..3acfe2d11 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006
    diff --git a/docs/articles/resistance_predict.html b/docs/articles/resistance_predict.html index a1b9a0051..8c5d30d05 100644 --- a/docs/articles/resistance_predict.html +++ b/docs/articles/resistance_predict.html @@ -39,7 +39,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006
    diff --git a/docs/articles/welcome_to_AMR.html b/docs/articles/welcome_to_AMR.html index 9fcec226e..770721231 100644 --- a/docs/articles/welcome_to_AMR.html +++ b/docs/articles/welcome_to_AMR.html @@ -39,7 +39,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006
    diff --git a/docs/authors.html b/docs/authors.html index c279bb902..b27109563 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -81,7 +81,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006
    diff --git a/docs/index.html b/docs/index.html index 532b087a7..b6cf25f14 100644 --- a/docs/index.html +++ b/docs/index.html @@ -43,7 +43,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006
    diff --git a/docs/news/index.html b/docs/news/index.html index a8e196cb1..40765d3e4 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 @@ -236,13 +236,13 @@ Source: NEWS.md -
    -

    -AMR 1.3.0.9005 Unreleased +
    +

    +AMR 1.3.0.9006 Unreleased

    -
    +

    -Last updated: 17 August 2020 +Last updated: 21 August 2020

    diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index cd8971df9..bb42e8f4d 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -2,7 +2,7 @@ pandoc: 2.7.3 pkgdown: 1.5.1.9000 pkgdown_sha: eae56f08694abebf93cdfc0dd8e9ede06d8c815f articles: [] -last_built: 2020-08-17T19:18Z +last_built: 2020-08-21T09:34Z urls: reference: https://msberends.github.io/AMR/reference article: https://msberends.github.io/AMR/articles diff --git a/docs/reference/AMR-deprecated.html b/docs/reference/AMR-deprecated.html index 7aa64a120..e72f1e4b0 100644 --- a/docs/reference/AMR-deprecated.html +++ b/docs/reference/AMR-deprecated.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006

    @@ -118,6 +118,13 @@ Predict antimicrobial resistance

    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/AMR.html b/docs/reference/AMR.html index 2b6eb132d..e415b85dc 100644 --- a/docs/reference/AMR.html +++ b/docs/reference/AMR.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -261,6 +268,11 @@

  • Principal component analysis for AMR

    • +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/WHOCC.html b/docs/reference/WHOCC.html index a0d04162e..4b1c7269a 100644 --- a/docs/reference/WHOCC.html +++ b/docs/reference/WHOCC.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/WHONET.html b/docs/reference/WHONET.html index d51061b7f..a3159984c 100644 --- a/docs/reference/WHONET.html +++ b/docs/reference/WHONET.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -269,6 +276,11 @@

  • AMP_ND10:CIP_EE
    28 different antibiotics. You can lookup the abbreviations in the     antibiotics data set, or use e.g. ab_name("AMP") to get the official name immediately. Before analysis, you should transform this to a valid antibiotic class, using as.rsi().

    • +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/ab_from_text.html b/docs/reference/ab_from_text.html index 73d5b1a2f..9cfec18d2 100644 --- a/docs/reference/ab_from_text.html +++ b/docs/reference/ab_from_text.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/ab_property.html b/docs/reference/ab_property.html index 942b1403b..8264c0cdb 100644 --- a/docs/reference/ab_property.html +++ b/docs/reference/ab_property.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -326,6 +333,11 @@ The lifecycle of this function is stableWorld Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: https://www.whocc.no/atc_ddd_index/

    WHONET 2019 software: http://www.whonet.org/software.html

    European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: http://ec.europa.eu/health/documents/community-register/html/atc.htm

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/age.html b/docs/reference/age.html index dd2962af4..087963122 100644 --- a/docs/reference/age.html +++ b/docs/reference/age.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/age_groups.html b/docs/reference/age_groups.html index 0f88a4f08..a89bc7d37 100644 --- a/docs/reference/age_groups.html +++ b/docs/reference/age_groups.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/antibiotic_class_selectors.html b/docs/reference/antibiotic_class_selectors.html index baadcf72c..fd545e448 100644 --- a/docs/reference/antibiotic_class_selectors.html +++ b/docs/reference/antibiotic_class_selectors.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -276,6 +283,11 @@

    All columns will be searched for known antibiotic names, abbreviations, brand names and codes (ATC, EARS-Net, WHO, etc.). This means that a selector like e.g. aminoglycosides() will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.

    These functions only work if the tidyselect package is installed, that comes with the dplyr package. An error will be thrown if tidyselect package is not installed, or if the functions are used outside a function that allows Tidyverse selections like select() or pivot_longer().

    +

    Read more on our website!

    + + + +

    On our website https://msberends.github.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data. As we would like to better understand the backgrounds and needs of our users, please participate in our survey!

    See also

    filter_ab_class() for the filter() equivalent.

    diff --git a/docs/reference/antibiotics.html b/docs/reference/antibiotics.html index 482ee81bd..b58b97e1c 100644 --- a/docs/reference/antibiotics.html +++ b/docs/reference/antibiotics.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9003 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -301,6 +308,11 @@ +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    WHOCC

    diff --git a/docs/reference/as.ab.html b/docs/reference/as.ab.html index 02cf04f05..f6c78ea9a 100644 --- a/docs/reference/as.ab.html +++ b/docs/reference/as.ab.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9003 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -296,6 +303,11 @@ This package contains all ~550 antibiotic, antimycotic and antiviral dru

    These have become the gold standard for international drug utilisation monitoring and research.

    The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.

    NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See https://www.whocc.no/copyright_disclaimer/.

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/as.disk.html b/docs/reference/as.disk.html index acdb7c4cd..38174ce7d 100644 --- a/docs/reference/as.disk.html +++ b/docs/reference/as.disk.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/as.mic.html b/docs/reference/as.mic.html index 432e840fd..5c3280a50 100644 --- a/docs/reference/as.mic.html +++ b/docs/reference/as.mic.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/as.mo.html b/docs/reference/as.mo.html index fb2d4251a..80ce7b38c 100644 --- a/docs/reference/as.mo.html +++ b/docs/reference/as.mo.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -374,6 +381,11 @@ The lifecycle of this function is stable
    This package contains the complete taxonomic tree of almost all microorganisms (~70,000 species) from the authoritative and comprehensive Catalogue of Life (http://www.catalogueoflife.org). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.

    Click here for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with catalogue_of_life_version().

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/as.rsi.html b/docs/reference/as.rsi.html index 67485157e..c1b7bde9c 100644 --- a/docs/reference/as.rsi.html +++ b/docs/reference/as.rsi.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 @@ -393,6 +393,11 @@ A microorganism is categorised as Susceptible, Increased exposure when


    The lifecycle of this function is stable. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.

    If the unlying code needs breaking changes, they will occur gradually. For example, a parameter will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/atc_online.html b/docs/reference/atc_online.html index ad3ac8cf4..8a7f02cd5 100644 --- a/docs/reference/atc_online.html +++ b/docs/reference/atc_online.html @@ -83,7 +83,7 @@ This function requires an internet connection." /> AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -119,6 +119,13 @@ This function requires an internet connection." /> Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/availability.html b/docs/reference/availability.html index 3c49f7090..5b89bb830 100644 --- a/docs/reference/availability.html +++ b/docs/reference/availability.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/bug_drug_combinations.html b/docs/reference/bug_drug_combinations.html index 551eafba1..e100a4d11 100644 --- a/docs/reference/bug_drug_combinations.html +++ b/docs/reference/bug_drug_combinations.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/catalogue_of_life.html b/docs/reference/catalogue_of_life.html index 1432c7ceb..0dd8afa87 100644 --- a/docs/reference/catalogue_of_life.html +++ b/docs/reference/catalogue_of_life.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/catalogue_of_life_version.html b/docs/reference/catalogue_of_life_version.html index 8f133dcf1..1aef4ce66 100644 --- a/docs/reference/catalogue_of_life_version.html +++ b/docs/reference/catalogue_of_life_version.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/count.html b/docs/reference/count.html index 340a25104..5dca00380 100644 --- a/docs/reference/count.html +++ b/docs/reference/count.html @@ -83,7 +83,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible( AMR (for R) - 1.3.0.9003 + 1.3.0.9006 @@ -119,6 +119,13 @@ count_resistant() should be used to count resistant isolates, count_susceptible( Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -233,7 +240,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
    -

    These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, please see Examples.

    +

    These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in summarise() from the dplyr package and also support grouped variables, please see Examples.

    count_resistant() should be used to count resistant isolates, count_susceptible() should be used to count susceptible isolates.

    diff --git a/docs/reference/eucast_rules.html b/docs/reference/eucast_rules.html index 470d1d295..d33f6c3a2 100644 --- a/docs/reference/eucast_rules.html +++ b/docs/reference/eucast_rules.html @@ -83,7 +83,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -119,6 +119,13 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -399,6 +406,11 @@ Leclercq et al. EUCAST expert rules in antimicrobial susceptibility test


    The     lifecycle of this function is maturing. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome to suggest changes at our repository or write us an email (see section 'Contact Us').

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/example_isolates.html b/docs/reference/example_isolates.html index 2b0ac055a..f61030df3 100644 --- a/docs/reference/example_isolates.html +++ b/docs/reference/example_isolates.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -253,6 +260,11 @@

  • PEN:RIF
    40 different antibiotics with class     rsi (see as.rsi()); these column names occur in the antibiotics data set and can be translated with ab_name()

    • +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/example_isolates_unclean.html b/docs/reference/example_isolates_unclean.html index 4222b1629..6bf854451 100644 --- a/docs/reference/example_isolates_unclean.html +++ b/docs/reference/example_isolates_unclean.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance +
  • + + + + Download our reference data sets for own use + +
  • @@ -248,6 +255,11 @@

  • AMX:GEN
    4 different antibiotics that have to be transformed with     as.rsi()

    • +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/filter_ab_class.html b/docs/reference/filter_ab_class.html index 0c80155b4..3e057353c 100644 --- a/docs/reference/filter_ab_class.html +++ b/docs/reference/filter_ab_class.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/first_isolate.html b/docs/reference/first_isolate.html index 1eb81ed8f..f7a55c120 100644 --- a/docs/reference/first_isolate.html +++ b/docs/reference/first_isolate.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/g.test.html b/docs/reference/g.test.html index d54808661..72d580faa 100644 --- a/docs/reference/g.test.html +++ b/docs/reference/g.test.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/ggplot_pca.html b/docs/reference/ggplot_pca.html index a9dd7a8df..e9b11ff51 100644 --- a/docs/reference/ggplot_pca.html +++ b/docs/reference/ggplot_pca.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/ggplot_rsi.html b/docs/reference/ggplot_rsi.html index daaeb3a02..c5ca4b385 100644 --- a/docs/reference/ggplot_rsi.html +++ b/docs/reference/ggplot_rsi.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/guess_ab_col.html b/docs/reference/guess_ab_col.html index 8b413ae18..73412f146 100644 --- a/docs/reference/guess_ab_col.html +++ b/docs/reference/guess_ab_col.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/index.html b/docs/reference/index.html index cd74c044b..5027368ee 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 diff --git a/docs/reference/intrinsic_resistant.html b/docs/reference/intrinsic_resistant.html index 8d5373154..a0d04a8ed 100644 --- a/docs/reference/intrinsic_resistant.html +++ b/docs/reference/intrinsic_resistant.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9004 + 1.3.0.9006 @@ -122,7 +122,7 @@ - Download our free data sets + Download our reference data sets for own use
  • @@ -256,6 +256,11 @@

    The repository of this AMR package contains a file comprising this exact data set: https://github.com/msberends/AMR/blob/master/data-raw/intrinsic_resistant.txt. This file allows for machine reading EUCAST guidelines about intrinsic resistance, which is almost impossible with the Excel and PDF files distributed by EUCAST. The file is updated automatically.

    This data set is based on 'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes', version 3.1, 2016.

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/join.html b/docs/reference/join.html index 62f15d42f..ebcb2aada 100644 --- a/docs/reference/join.html +++ b/docs/reference/join.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/key_antibiotics.html b/docs/reference/key_antibiotics.html index 5777b3ec4..a72e258c1 100644 --- a/docs/reference/key_antibiotics.html +++ b/docs/reference/key_antibiotics.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/kurtosis.html b/docs/reference/kurtosis.html index ce2da813e..604cdf2e7 100644 --- a/docs/reference/kurtosis.html +++ b/docs/reference/kurtosis.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/lifecycle.html b/docs/reference/lifecycle.html index 2b352ddfe..52d575fca 100644 --- a/docs/reference/lifecycle.html +++ b/docs/reference/lifecycle.html @@ -84,7 +84,7 @@ This page contains a section for every lifecycle (with text borrowed from the af AMR (for R) - 1.3.0.9003 + 1.3.0.9006 @@ -120,6 +120,13 @@ This page contains a section for every lifecycle (with text borrowed from the af Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/like.html b/docs/reference/like.html index 22e664c0d..17a95d4af 100644 --- a/docs/reference/like.html +++ b/docs/reference/like.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/mdro.html b/docs/reference/mdro.html index b18eb10f2..61a7e8569 100644 --- a/docs/reference/mdro.html +++ b/docs/reference/mdro.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/microorganisms.codes.html b/docs/reference/microorganisms.codes.html index c94c5e147..515360bd6 100644 --- a/docs/reference/microorganisms.codes.html +++ b/docs/reference/microorganisms.codes.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -245,6 +252,11 @@

  • mo
    ID of the microorganism in the     microorganisms data set

    • +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Catalogue of Life

    diff --git a/docs/reference/microorganisms.html b/docs/reference/microorganisms.html index bfc893e64..7068a1712 100644 --- a/docs/reference/microorganisms.html +++ b/docs/reference/microorganisms.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9003 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance +
  • + + + + Download our reference data sets for own use + +
  • @@ -295,6 +302,11 @@


    This package contains the complete taxonomic tree of almost all microorganisms (~70,000 species) from the authoritative and comprehensive Catalogue of Life (    http://www.catalogueoflife.org). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.

    Click here for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with catalogue_of_life_version().

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/microorganisms.old.html b/docs/reference/microorganisms.old.html index cc31b91b0..07cb42bb3 100644 --- a/docs/reference/microorganisms.old.html +++ b/docs/reference/microorganisms.old.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -258,6 +265,11 @@


    This package contains the complete taxonomic tree of almost all microorganisms (~70,000 species) from the authoritative and comprehensive Catalogue of Life (    http://www.catalogueoflife.org). The Catalogue of Life is the most comprehensive and authoritative global index of species currently available.

    Click here for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with catalogue_of_life_version().

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/mo_property.html b/docs/reference/mo_property.html index 9bd09f2b0..40b490136 100644 --- a/docs/reference/mo_property.html +++ b/docs/reference/mo_property.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • @@ -357,6 +364,11 @@ This package contains the complete taxonomic tree of almost all microorganisms (

  • Catalogue of Life: Annual Checklist (public online taxonomic database), http://www.catalogueoflife.org (check included annual version with catalogue_of_life_version()).

    • +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/mo_source.html b/docs/reference/mo_source.html index 64cc1d3b7..b9d9627e9 100644 --- a/docs/reference/mo_source.html +++ b/docs/reference/mo_source.html @@ -83,7 +83,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -119,6 +119,13 @@ This is the fastest way to have your organisation (or analysis) specific codes p Predict antimicrobial resistance +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/p_symbol.html b/docs/reference/p_symbol.html index 78b8ff6d6..dde9e8ef1 100644 --- a/docs/reference/p_symbol.html +++ b/docs/reference/p_symbol.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/pca.html b/docs/reference/pca.html index 1c676efe0..a10287b96 100644 --- a/docs/reference/pca.html +++ b/docs/reference/pca.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/proportion.html b/docs/reference/proportion.html index f275a2561..92075e720 100644 --- a/docs/reference/proportion.html +++ b/docs/reference/proportion.html @@ -83,7 +83,7 @@ resistance() should be used to calculate resistance, susceptibility() should be AMR (for R) - 1.3.0.9003 + 1.3.0.9006 @@ -119,6 +119,13 @@ resistance() should be used to calculate resistance, susceptibility() should be Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/resistance_predict.html b/docs/reference/resistance_predict.html index 66eef367b..246bcd0ce 100644 --- a/docs/reference/resistance_predict.html +++ b/docs/reference/resistance_predict.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/rsi_translation.html b/docs/reference/rsi_translation.html index e076b0159..87de2770f 100644 --- a/docs/reference/rsi_translation.html +++ b/docs/reference/rsi_translation.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 @@ -263,6 +263,11 @@

    Details

    The repository of this AMR package contains a file comprising this exact data set: https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt. This file allows for machine reading EUCAST and CLSI guidelines, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically.

    +

    Reference data publicly available

    + + + +

    All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this AMR package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find all download links on our website, which is automatically updated with every code change.

    Read more on our website!

    diff --git a/docs/reference/skewness.html b/docs/reference/skewness.html index 68dea2b8c..31b7fb1b2 100644 --- a/docs/reference/skewness.html +++ b/docs/reference/skewness.html @@ -83,7 +83,7 @@ When negative: the left tail is longer; the mass of the distribution is concentr AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -119,6 +119,13 @@ When negative: the left tail is longer; the mass of the distribution is concentr Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/reference/translate.html b/docs/reference/translate.html index 81cc1b635..90457980f 100644 --- a/docs/reference/translate.html +++ b/docs/reference/translate.html @@ -82,7 +82,7 @@ AMR (for R) - 1.3.0.9002 + 1.3.0.9006 @@ -118,6 +118,13 @@ Predict antimicrobial resistance
    • +
  • + + + + Download our reference data sets for own use + +
  • diff --git a/docs/survey.html b/docs/survey.html index 6f2034892..910af8440 100644 --- a/docs/survey.html +++ b/docs/survey.html @@ -81,7 +81,7 @@ AMR (for R) - 1.3.0.9005 + 1.3.0.9006 diff --git a/man/AMR.Rd b/man/AMR.Rd index f8a7948ba..3de97761e 100644 --- a/man/AMR.Rd +++ b/man/AMR.Rd @@ -33,6 +33,11 @@ This package can be used for: \item Principal component analysis for AMR } } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/WHONET.Rd b/man/WHONET.Rd index 60040285f..c8c03740f 100644 --- a/man/WHONET.Rd +++ b/man/WHONET.Rd @@ -41,6 +41,11 @@ WHONET \description{ This example data set has the exact same structure as an export file from WHONET. Such files can be used with this package, as this example data set shows. The data itself was based on our \link{example_isolates} data set. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/ab_property.Rd b/man/ab_property.Rd index 5cef1b7fc..19d33c19d 100644 --- a/man/ab_property.Rd +++ b/man/ab_property.Rd @@ -93,6 +93,11 @@ WHONET 2019 software: \url{http://www.whonet.org/software.html} European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: \url{http://ec.europa.eu/health/documents/community-register/html/atc.htm} } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/antibiotic_class_selectors.Rd b/man/antibiotic_class_selectors.Rd index be67d3569..49e9c0b98 100644 --- a/man/antibiotic_class_selectors.Rd +++ b/man/antibiotic_class_selectors.Rd @@ -57,6 +57,11 @@ All columns will be searched for known antibiotic names, abbreviations, brand na These functions only work if the \code{tidyselect} package is installed, that comes with the \code{dplyr} package. An error will be thrown if \code{tidyselect} package is not installed, or if the functions are used outside a function that allows Tidyverse selections like \code{select()} or \code{pivot_longer()}. } +\section{Read more on our website!}{ + +On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! +} + \examples{ \dontrun{ library(dplyr) diff --git a/man/antibiotics.Rd b/man/antibiotics.Rd index 3293928c8..53d37d6b3 100644 --- a/man/antibiotics.Rd +++ b/man/antibiotics.Rd @@ -75,6 +75,11 @@ Files in R format (with preserved data structure) can be found here: } } } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{WHOCC}{ \if{html}{\figure{logo_who.png}{options: height=60px style=margin-bottom:5px} \cr} diff --git a/man/as.ab.Rd b/man/as.ab.Rd index 9d197a6e0..f53ff8025 100644 --- a/man/as.ab.Rd +++ b/man/as.ab.Rd @@ -65,6 +65,11 @@ The WHOCC is located in Oslo at the Norwegian Institute of Public Health and fun \strong{NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package.} See \url{https://www.whocc.no/copyright_disclaimer/.} } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/as.mo.Rd b/man/as.mo.Rd index 22dd7f790..694911c07 100644 --- a/man/as.mo.Rd +++ b/man/as.mo.Rd @@ -146,6 +146,11 @@ This package contains the complete taxonomic tree of almost all microorganisms ( \link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with \code{\link[=catalogue_of_life_version]{catalogue_of_life_version()}}. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/as.rsi.Rd b/man/as.rsi.Rd index 07be30bf5..a1d713efb 100755 --- a/man/as.rsi.Rd +++ b/man/as.rsi.Rd @@ -142,6 +142,11 @@ The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stabl If the unlying code needs breaking changes, they will occur gradually. For example, a parameter will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/eucast_rules.Rd b/man/eucast_rules.Rd index 13893a70f..c418ed3c9 100644 --- a/man/eucast_rules.Rd +++ b/man/eucast_rules.Rd @@ -159,6 +159,11 @@ The following antibiotics are used for the functions \code{\link[=eucast_rules]{ The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unlying code of a maturing function has been roughed out, but finer details might still change. Since this function needs wider usage and more extensive testing, you are very welcome \href{https://github.com/msberends/AMR/issues}{to suggest changes at our repository} or \link[=AMR]{write us an email (see section 'Contact Us')}. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/example_isolates.Rd b/man/example_isolates.Rd index c8e401160..ac9511c20 100644 --- a/man/example_isolates.Rd +++ b/man/example_isolates.Rd @@ -25,6 +25,11 @@ example_isolates \description{ A data set containing 2,000 microbial isolates with their full antibiograms. The data set reflects reality and can be used to practice AMR analysis. For examples, please read \href{https://msberends.github.io/AMR/articles/AMR.html}{the tutorial on our website}. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/example_isolates_unclean.Rd b/man/example_isolates_unclean.Rd index d2ae9311f..674419d5a 100644 --- a/man/example_isolates_unclean.Rd +++ b/man/example_isolates_unclean.Rd @@ -20,6 +20,11 @@ example_isolates_unclean \description{ A data set containing 3,000 microbial isolates that are not cleaned up and consequently not ready for AMR analysis. This data set can be used for practice. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/intrinsic_resistant.Rd b/man/intrinsic_resistant.Rd index 1f2cefcc0..5bb12634c 100644 --- a/man/intrinsic_resistant.Rd +++ b/man/intrinsic_resistant.Rd @@ -22,6 +22,11 @@ The repository of this \code{AMR} package contains a file comprising this exact This data set is based on 'EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes', version 3.1, 2016. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/microorganisms.Rd b/man/microorganisms.Rd index 26a3e2e95..a18c77bda 100755 --- a/man/microorganisms.Rd +++ b/man/microorganisms.Rd @@ -72,6 +72,11 @@ This package contains the complete taxonomic tree of almost all microorganisms ( \link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with \code{\link[=catalogue_of_life_version]{catalogue_of_life_version()}}. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/microorganisms.codes.Rd b/man/microorganisms.codes.Rd index 27b36fe1e..d0c5314cb 100644 --- a/man/microorganisms.codes.Rd +++ b/man/microorganisms.codes.Rd @@ -17,6 +17,11 @@ microorganisms.codes \description{ A data set containing commonly used codes for microorganisms, from laboratory systems and WHONET. Define your own with \code{\link[=set_mo_source]{set_mo_source()}}. They will all be searched when using \code{\link[=as.mo]{as.mo()}} and consequently all the \code{\link[=mo_property]{mo_*}} functions. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Catalogue of Life}{ \if{html}{\figure{logo_col.png}{options: height=40px style=margin-bottom:5px} \cr} diff --git a/man/microorganisms.old.Rd b/man/microorganisms.old.Rd index bb2598327..d1a24b350 100644 --- a/man/microorganisms.old.Rd +++ b/man/microorganisms.old.Rd @@ -32,6 +32,11 @@ This package contains the complete taxonomic tree of almost all microorganisms ( \link[=catalogue_of_life]{Click here} for more information about the included taxa. Check which version of the Catalogue of Life was included in this package with \code{\link[=catalogue_of_life_version]{catalogue_of_life_version()}}. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/mo_property.Rd b/man/mo_property.Rd index 8f72e1875..523071db3 100644 --- a/man/mo_property.Rd +++ b/man/mo_property.Rd @@ -142,6 +142,11 @@ This package contains the complete taxonomic tree of almost all microorganisms ( } } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/man/rsi_translation.Rd b/man/rsi_translation.Rd index 00429732d..fc775b903 100644 --- a/man/rsi_translation.Rd +++ b/man/rsi_translation.Rd @@ -28,6 +28,11 @@ Data set to interpret MIC and disk diffusion to R/SI values. Included guidelines \details{ The repository of this \code{AMR} package contains a file comprising this exact data set: \url{https://github.com/msberends/AMR/blob/master/data-raw/rsi_translation.txt}. This file \strong{allows for machine reading EUCAST and CLSI guidelines}, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. The file is updated automatically. } +\section{Reference data publicly available}{ + +All reference data sets (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this \code{AMR} package are publicly and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply flat files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please find \href{https://msberends.github.io/AMR/articles/datasets.html}{all download links on our website}, which is automatically updated with every code change. +} + \section{Read more on our website!}{ On our website \url{https://msberends.github.io/AMR} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.github.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}. As we would like to better understand the backgrounds and needs of our users, please \href{https://msberends.github.io/AMR/survey.html}{participate in our survey}! diff --git a/vignettes/datasets.Rmd b/vignettes/datasets.Rmd index fdc183df5..ae69b0548 100644 --- a/vignettes/datasets.Rmd +++ b/vignettes/datasets.Rmd @@ -47,8 +47,8 @@ download_txt <- function(filename) { txt <- paste0(filename, ".txt") rds <- paste0(filename, ".rds") spss <- paste0(filename, ".sav") - stata <- paste0(filename, ".sav") - sas <- paste0(filename, ".dta") + stata <- paste0(filename, ".dta") + sas <- paste0(filename, ".sas") excel <- paste0(filename, ".xlsx") create_txt <- function(filename, type) { paste0("[", type, "](", github_base, filename, "), ", file_size(filename), " -- ") @@ -59,7 +59,7 @@ download_txt <- function(filename) { if (file.exists(spss)) msg <- c(msg, create_txt(spss, "SPSS file (.sav)")) if (file.exists(stata)) msg <- c(msg, create_txt(stata, "Stata file (.dta)")) if (file.exists(sas)) msg <- c(msg, create_txt(sas, "SAS file (.sas)")) - if (file.exists(txt)) msg <- c(msg, create_txt(txt, "Tab separated file (.txt)")) + if (file.exists(txt)) msg <- c(msg, create_txt(txt, "tab separated file (.txt)")) msg[length(msg)] <- gsub(" --", ".", msg[length(msg)], fixed = TRUE) paste0(msg, collapse = "") } @@ -90,11 +90,9 @@ print_df <- function(x) { ``` -This package contains a lot of reference data sets that are all reliable, up-to-date and free to download. You can even use them outside of R, for example to teach your laboratory information system (LIS) about intrinsic resistance! +All reference data (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) in this `AMR` package are reliable, up-to-date and freely available. We continually export our data sets to formats for use in R, SPSS, SAS, Stata and Excel. We also supply tab separated files that are machine-readable and suitable for input in any software program, such as laboratory information systems. -We included them in our `AMR` package, but also automatically 'mirror' them to our public repository in different software formats. On this page, we explain how to download them and how the structure of the data sets look like. The tab separated files **allow for machine reading taxonomic data and EUCAST and CLSI interpretation guidelines**, which is almost impossible with the Excel and PDF files distributed by EUCAST and CLSI. We also offer all data sets in formats for R, SPSS, SAS, Stata and Excel. - -*Note: Years and dates of updates mentioned on this page, are from on `AMR` package version `r utils::packageVersion("AMR")`, online released on `r format(utils::packageDate("AMR"), "%e %B %Y")`. **If you are reading this page from within R, please [visit our website](https://msberends.github.io/AMR/articles/datasets.html) for the latest update.*** +On this page, we explain how to download them and how the structure of the data sets look like. If you are reading this page from within R, please [visit our website](https://msberends.github.io/AMR/articles/datasets.html), which is automatically updated with every code change. ## Microorganisms (currently accepted names)